NewRocket

Deploy and scale AI-powered workflow solutions for enterprise clients collaborating with cross-functional teams. | 5-8 years software engineering experience with proficiency in Python or JavaScript/TypeScript and hands-on LLM application development. | Forward Deployed AI Engineer AI Foundry | NewRocket Location: Remote with travel (~25%) NewRocket NewRocket’s partnership with Anthropic gives our AI team access to leading-edge Claude technology and positions us at the forefront of enterprise AI adoption. You’ll work directly with clients to turn emerging AI capabilities into practical, scalable business solutions—combining strong engineering skills with a deep understanding of real-world business needs. Role Overview NewRocket is seeking a highly skilled Senior Forward Deployed AI Engineer to join the AI Foundry team and work directly with customers to deploy, operationalize, and scale AI-powered workflow solutions. This role blends full-stack engineering, enterprise integration, generative AI implementation, and client-facing solution delivery. Forward Deployed AI Engineers partner closely with business consultants, product teams, AI/ML engineers, and customer stakeholders to translate real-world business problems into secure, reliable, deployable AI-driven solutions. As an Anthropic partner/vendor, NewRocket is expanding its capability to design and deliver enterprise solutions using Claude and other leading AI technologies. In this role, you will apply modern LLM engineering practices—including prompt and context engineering, retrieval-augmented generation (RAG), tool use, structured outputs, agentic workflows, model evaluation, and responsible AI controls—to deliver measurable customer value. You will help customers implement agentic AI workflows, intelligent automations, and AI-powered integrations within ServiceNow and broader enterprise ecosystems. You will also contribute directly to the evolution of NewRocket’s AI platforms, accelerators, and intellectual property, including the NewRocket Intelligence Platform, Value Realization Dashboard, Data Intelligence Platform, and reusable Agent Packs. This role requires strong engineering skills, curiosity about emerging AI technologies, sound judgment regarding responsible AI deployment, and the ability to operate effectively in fast-moving customer environments. Key Responsibilities Client Delivery & AI Solution Implementation Deploy, configure, and operationalize agentic AI workflows, AI assistants, and AI-powered automations within client ServiceNow environments and enterprise technology ecosystems. Translate customer business requirements, operational processes, and desired outcomes into technical architectures, implementation plans, and production-ready AI solutions. Implement and integrate NewRocket Agent Packs, AI accelerators, and workflow solutions into enterprise environments. Work directly with customer teams to tailor AI solutions to their operating models, business processes, data sources, security requirements, and user needs. Support workshops, discovery sessions, technical working sessions, demonstrations, pilots, and production rollouts. Clearly communicate AI capabilities, limitations, tradeoffs, solution behavior, and adoption considerations to technical and business stakeholders. Anthropic and Generative AI Engineering Build enterprise AI applications and workflows using Claude, the Anthropic API, and other LLM platforms as appropriate for the client use case. Apply effective prompt and context-engineering techniques, including clear instructions, examples, role and task definition, structured inputs, response constraints, and long-context management. Design and implement AI workflows using structured outputs, tool use/function calling, API integrations, multi-step orchestration, and human-in-the-loop review patterns. Build retrieval-augmented generation (RAG) solutions that ground AI responses in authorized enterprise data and knowledge sources. Implement practical techniques to improve reliability and user trust, including citation or source-grounding patterns, validation, confidence thresholds, output schemas, fallback handling, and escalation workflows. Stay current on Anthropic platform capabilities, Claude model releases, implementation guidance, responsible AI principles, and enterprise deployment best practices. Complete relevant Anthropic training, partner enablement, and technical education programs as available, and incorporate those practices into NewRocket solution delivery. Solution Engineering & Prototyping Build demos, prototypes, and proof-of-concept implementations that validate AI-driven workflows and customer use cases. Rapidly iterate with customers and internal teams to refine AI-powered solutions based on feedback, performance results, and operational needs. Support the design and implementation of AI orchestration, LLM integrations, agentic decision models, and workflow automation patterns. Evaluate when an agentic approach is appropriate versus deterministic automation, traditional workflow logic, search, analytics, or human review. Develop reusable implementation patterns, solution templates, prompt libraries, integrations, and deployment assets that accelerate future client delivery. Full-Stack Engineering & Integration Develop secure integrations between ServiceNow, enterprise systems, APIs, data platforms, and AI services. Build supporting components such as scripts, microservices, automation logic, integration services, and lightweight user interfaces. Implement integrations with AI platforms, enterprise APIs, identity systems, document repositories, databases, and structured and unstructured data sources. Apply sound engineering practices for authentication, authorization, secrets management, access controls, logging, error handling, version control, and documentation. Design solutions that meet enterprise expectations for security, scalability, maintainability, observability, and production readiness. AI Quality, Evaluation & Responsible AI Develop and execute practical evaluation approaches for AI applications, including test cases, representative datasets, success metrics, and regression testing. Assess AI workflow quality across dimensions such as relevance, accuracy, groundedness, task completion, safety, latency, cost, and user experience. Implement safeguards for sensitive data, role-based permissions, appropriate data access, prompt injection risks, unsafe tool use, and unintended model behavior. Establish human-in-the-loop workflows for sensitive, high-impact, low-confidence, or exception-based decisions. Document AI solution behavior, known limitations, risk controls, governance considerations, and operational support procedures. Monitor and improve deployed solutions based on user feedback, usage patterns, performance data, incidents, and evolving customer needs. Product & Platform Contribution Actively contribute to the development and evolution of NewRocket’s AI intellectual property and platforms, including: NewRocket Intelligence Platform Value Realization Dashboard Data Intelligence Platform Agent Packs and reusable AI solution accelerators Responsibilities include: Identifying common patterns, requirements, integration needs, and capabilities discovered through customer deployments. Contributing reusable assets, integration components, prompt patterns, evaluation frameworks, and automation capabilities. Providing actionable product feedback that improves usability, reliability, scalability, security, and customer value. Helping transform successful client implementations into repeatable platform features, accelerators, and delivery playbooks. Supporting the definition of standards and best practices for enterprise AI delivery across NewRocket’s AI Foundry. Systems Integration & Troubleshooting Diagnose and resolve technical issues across AI workflows, integrations, retrieval pipelines, data connections, and automation processes. Troubleshoot issues related to model inputs and outputs, prompt behavior, tool execution, API reliability, permissions, data quality, and system performance. Ensure deployed AI solutions are secure, scalable, supportable, and production-ready. Optimize deployed systems for reliability, performance, latency, model usage, and cost efficiency. Cross-Team Collaboration Work closely with Business Process Consultants, Product Engineering, Data Engineers, AI/ML Engineers, ServiceNow teams, and the AI Center of Excellence. Serve as the engineering counterpart to consulting and delivery teams throughout discovery, solution design, implementation, rollout, and continuous improvement. Contribute to internal playbooks, technical documentation, reusable deployment patterns, reference architectures, and product evolution. Share lessons learned from customer deployments to strengthen NewRocket’s AI delivery capabilities and solution portfolio. What Success Looks Like in the First 6 Months Successfully deploy AI-powered workflows, assistants, automations, or integrations across multiple customer engagements. Deliver secure, reliable AI workflows within customer ServiceNow environments and connected enterprise systems. Build trusted relationships with customer technical teams, business stakeholders, and NewRocket delivery teams. Demonstrate strong practical application of Claude and modern LLM engineering practices, including prompt/context engineering, tool use, RAG, evaluations, and responsible AI controls. Contribute reusable components, implementation patterns, prompt assets, and improvements to NewRocket’s AI platforms and accelerators. Provide actionable customer-driven feedback that improves the NewRocket Intelligence Platform and related products. Help establish repeatable methods for moving AI use cases from prototype through governed production deployment. Required Qualifications 5-8 years of experience in software engineering, systems integration, enterprise platforms, workflow automation, or related technical delivery roles. Strong engineering foundation, with hands-on experience in full-stack development, scripting, APIs, microservices, enterprise integrations, or cloud-native applications. Experience building, deploying, or supporting AI/LLM-powered applications, AI-enabled automations, conversational experiences, RAG systems, or agentic workflows. Experience integrating APIs, enterprise applications, data platforms, or workflow systems in production environments. Proficiency in JavaScript/TypeScript, Python, or similar programming and scripting languages. Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud. Familiarity with modern LLM application concepts, including prompt engineering, context windows, token usage, embeddings, vector search, RAG, tool use/function calling, structured outputs, and model evaluation. Understanding of responsible AI concepts, including hallucination mitigation, sensitive-data handling, identity and access controls, human oversight, AI safety, and secure AI deployment. Experience operating in customer-facing engineering, consulting, technical implementation, solutions architecture, or professional-services roles. Strong problem-solving skills and the ability to communicate complex technical concepts clearly to both technical and business stakeholders. Ability to manage ambiguity, prioritize effectively, travel approximately 25%, and deliver high-quality solutions in fast-moving customer environments. Preferred Qualifications Anthropic / Claude Experience Hands-on experience with the Anthropic API, Claude models, Anthropic Console, Claude Code, or Anthropic implementation guidance. Completion of relevant Anthropic Academy learning, partner enablement, technical training, or equivalent hands-on experience deploying Claude-based solutions. Experience applying Claude capabilities such as long-context processing, tool use, structured outputs, document analysis, and enterprise knowledge workflows. Familiarity with Model Context Protocol (MCP) concepts and experience building or integrating secure tools and data connections for AI applications. ServiceNow Experience — Strong Plus Experience with ServiceNow development, configuration, workflow automation, or enterprise platform implementation. Familiarity with ServiceNow scripting, APIs, IntegrationHub, Flow Designer, Virtual Agent, Now Assist, AI Agents, and platform development patterns. Understanding of ServiceNow data models and enterprise workflow concepts, including: CMDB ITSM, CSM, HRSD, or employee workflows Workflow and task tables Knowledge management Enterprise integrations and data exchange patterns AI, Data & Platform Experience Experience building AI prototypes, RAG systems, semantic search capabilities, AI assistants, or agent-based workflows. Experience integrating LLM APIs or AI services into enterprise applications and business processes. Experience with vector databases, embeddings, document ingestion, chunking, retrieval strategies, and knowledge-grounding patterns. Familiarity with LLM orchestration and application frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or comparable tools. Experience with AI observability, tracing, evaluation frameworks, prompt/version management, monitoring, and cost optimization. Experience contributing to internal platforms, reusable accelerators, developer tooling, or product capabilities. Familiarity with Docker, CI/CD, SQL, Git, infrastructure-as-code, and secure cloud deployment practices. Why This Role Matters Forward Deployed AI Engineers are the bridge between real-world enterprise problems and NewRocket’s AI platforms. By working directly with customers, they deliver immediate operational value while shaping the evolution of NewRocket’s AI products, accelerators, and platform capabilities. This role is critical to scaling the NewRocket Intelligence Platform and the broader AI Foundry strategy. As NewRocket expands its partnership with Anthropic, this engineer will help establish practical, secure, and responsible patterns for deploying Claude-powered AI solutions that improve enterprise workflows, accelerate decision-making, and create measurable business outcomes. We Take Care of Our People NewRocket is committed to a diverse and inclusive workplace. We value and celebrate diversity, believing that every employee matters and should be respected and heard. We are proud to be an equal opportunity workplace and affirmative action employer, committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin, or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, citizenship, military, or Veteran status. For individuals with disabilities who would like to request an accommodation, please contact hr.us@newrocket.com.

Design and maintain scalable AI platform capabilities supporting enterprise AI and LLM workflows with cross-team collaboration. | 5+ years in platform, cloud, or software engineering with expertise in cloud-native apps, AI/ML frameworks, programming, CI/CD, and containerization. | AI Platform Engineer-Anthropic AI Foundry | NewRocket Location: [Location / Hybrid / Remote] Travel based on client and business needs Reports to: Global AI Center of Excellence Lead / AI Platform Architect About NewRocket NewRocket is the AI-first Elite ServiceNow Partner that activates real value on the Now Platform. As a trusted advisor to enterprise leaders, we combine industry expertise, human-centered design, and enterprise-grade AI to help organizations navigate change and scale with confidence. With two decades of experience guiding clients to realize the full potential of the ServiceNow AI Platform, NewRocket is one of the largest pure-play ServiceNow partners. We are uniquely focused on enabling enterprises to adopt AI they trust—AI that delivers lasting business value. NewRocket is proud to be an Anthropic partner/vendor. Through this relationship, we are expanding our ability to help enterprise clients responsibly design, deploy, and scale AI solutions powered by Claude and other leading AI technologies. Our AI Foundry teams apply Anthropic-aligned practices across prompt and context engineering, retrieval-augmented generation (RAG), agentic workflows, tool use, structured outputs, model evaluation, security, governance, and human-in-the-loop controls. We #GoBeyondWorkflows to create new kinds of experiences for our customers. Come join our Crew! Role Overview NewRocket is seeking an experienced AI Platform Engineer to build, operate, and continuously improve the technical foundations that enable secure, reliable, scalable enterprise AI solutions. This role combines cloud engineering, platform engineering, DevOps, MLOps/LLMOps, data-platform integration, and applied AI engineering. The AI Platform Engineer will work closely with AI Architects, Forward Deployed AI Engineers, data engineers, ServiceNow teams, product engineering, and customer stakeholders to create reusable platforms, deployment patterns, controls, and operational capabilities for NewRocket’s Anthropic and enterprise AI business. You will help establish the infrastructure and engineering practices required to move AI solutions from prototype to governed production use. This includes enabling Claude and other LLM-powered applications; supporting RAG and agentic workflows; integrating enterprise data and tools; implementing observability and evaluation; and maintaining strong security, privacy, and governance controls. The ideal candidate is a hands-on engineer who is comfortable working across cloud infrastructure, APIs, CI/CD, data systems, containers, AI application frameworks, and enterprise security requirements. You are equally motivated by building reusable internal capabilities and solving practical customer-delivery challenges. Key Responsibilities AI Platform Architecture & Engineering Design, build, deploy, and maintain scalable platform capabilities that support enterprise AI, machine learning, LLM, RAG, and agentic AI applications. Create reusable reference architectures, infrastructure patterns, deployment templates, integration components, and engineering standards for NewRocket’s AI Foundry. Build platform capabilities that enable AI applications to securely connect to enterprise data, APIs, workflow systems, and authorized tools. Partner with AI Architects and Forward Deployed AI Engineers to translate client needs into reliable, supportable technical platform designs. Support the technical evolution of NewRocket’s AI intellectual property, including the NewRocket Intelligence Platform, Data Intelligence Platform, Value Realization Dashboard, Agent Packs, and reusable AI accelerators. Evaluate and recommend cloud, data, AI, observability, orchestration, and security technologies that improve delivery speed, quality, scalability, and cost efficiency. Anthropic, Claude & LLM Platform Enablement Build and maintain secure, reusable integrations with the Anthropic API, Claude models, and other approved AI services. Enable LLM-powered applications through standardized patterns for authentication, model access, prompt and context management, structured outputs, tool use, logging, error handling, and rate-limit management. Support Claude-based enterprise use cases involving document analysis, knowledge assistance, workflow automation, agentic task execution, summarization, classification, and decision support. Develop technical patterns for long-context workflows, document processing, RAG, structured data extraction, and model-driven automation. Support secure Model Context Protocol (MCP) and comparable tool-integration patterns that allow AI applications to access approved enterprise systems and data safely. Stay current on Anthropic platform capabilities, product releases, security guidance, technical enablement, and responsible AI practices. Complete relevant Anthropic partner training and enablement as available and help translate learning into reusable NewRocket engineering standards. LLMOps, MLOps & AI Operations Establish and operate CI/CD pipelines for AI applications, model configurations, prompts, evaluation assets, infrastructure, and integration services. Implement versioning, testing, release-management, rollback, and change-control practices for AI solutions. Build and maintain LLMOps and MLOps capabilities, including model/prompt configuration management, evaluation pipelines, deployment automation, monitoring, and lifecycle management. Develop automated evaluation and regression-testing frameworks to measure AI quality before and after releases. Support production operations for AI services, including incident response, troubleshooting, root-cause analysis, capacity planning, and service-level monitoring. Define and monitor operational metrics such as availability, latency, throughput, token consumption, model cost, tool-call success rates, task-completion rates, and error rates. Improve platform reliability, performance, resilience, and cost efficiency through automation, tuning, and operational improvements. Cloud Infrastructure, DevOps & Security Design and manage cloud infrastructure across AWS, Microsoft Azure, Google Cloud Platform, or client-approved environments. Build and maintain infrastructure using infrastructure-as-code tools such as Terraform, CloudFormation, Bicep, Pulumi, or comparable technologies. Implement containerized application and AI-service deployments using Docker, Kubernetes, serverless services, and cloud-native application patterns. Develop secure CI/CD workflows using Git-based source control, automated testing, artifact management, secrets management, and policy controls. Implement identity, access, and authentication patterns, including role-based access control, least-privilege access, API security, service accounts, and credential rotation. Partner with security, compliance, and client teams to ensure AI platforms align with enterprise security, privacy, regulatory, and data-residency requirements. Implement logging, monitoring, auditing, vulnerability management, disaster-recovery, and business-continuity practices for production AI services. Data Platform & RAG Enablement Build and support secure data-ingestion, transformation, indexing, and retrieval pipelines for enterprise AI applications. Design platform patterns for RAG, including document ingestion, parsing, chunking, metadata enrichment, embeddings, vector stores, hybrid search, retrieval, reranking, and source attribution. Integrate AI applications with structured and unstructured enterprise data sources, including databases, data warehouses, document repositories, knowledge bases, ServiceNow, and third-party SaaS platforms. Work with data engineers to establish data-quality, lineage, cataloging, permissions, retention, and governance practices that support trustworthy AI. Enable appropriate data-access controls so AI solutions retrieve and process only data the requesting user or service is authorized to access. Support data platforms and technologies such as Snowflake, Databricks, PostgreSQL, MongoDB, Elasticsearch/OpenSearch, vector databases, and cloud storage services, as appropriate. Responsible AI, Governance & Observability Implement technical controls that support responsible, secure, and governable AI deployments. Build safeguards for sensitive-data handling, data masking, content filtering, prompt injection, unsafe tool use, unauthorized access, and unintended agent behavior. Enable grounding, output validation, source attribution, confidence thresholds, fallback behavior, approval gates, and human-in-the-loop workflows. Implement AI observability and tracing across prompts, model calls, retrieval pipelines, tool execution, workflow outcomes, latency, errors, costs, and user feedback. Partner with AI Architects and governance stakeholders to document platform standards, risk controls, operating procedures, and solution limitations. Support auditability and compliance requirements through appropriate logging, retention, access reviews, and operational documentation. Enterprise Integration & ServiceNow Enablement Build and maintain integration patterns between AI platforms, ServiceNow, enterprise APIs, identity providers, workflow tools, collaboration platforms, and line-of-business systems. Support technical enablement for ServiceNow AI and workflow experiences, including IntegrationHub, Flow Designer, Virtual Agent, Now Assist, AI Agents, APIs, and knowledge-management capabilities where applicable. Develop secure APIs, middleware services, event-driven integrations, and automation components that support AI-enabled workflows. Collaborate with Forward Deployed AI Engineers to troubleshoot complex client integrations and transition successful engagement solutions into reusable platform components. Collaboration & Technical Leadership Work closely with AI Architects, AI/ML Engineers, Data Engineers, Product Engineering, ServiceNow developers, Business Process Consultants, and client technology teams. Provide technical guidance on AI platform engineering, cloud architecture, DevOps, LLMOps, data integration, performance, and security best practices. Contribute to internal playbooks, runbooks, reference architectures, technical documentation, reusable modules, and knowledge-sharing sessions. Identify recurring client requirements and convert them into scalable, productized platform features and accelerators. Participate in technical discovery, architecture reviews, demos, implementation planning, and customer workshops as needed. What Success Looks Like in the First 6 Months Establish or enhance reusable, secure deployment patterns for Claude-powered and other enterprise AI applications. Deliver reliable cloud, integration, data, and observability capabilities that support multiple AI Foundry client engagements. Implement CI/CD, infrastructure-as-code, monitoring, and LLMOps practices that improve deployment speed, quality, and operational maturity. Enable secure RAG, tool-use, and agentic AI patterns that integrate effectively with ServiceNow and enterprise ecosystems. Help productionize AI solutions through robust testing, evaluation, governance, access controls, and operational support practices. Contribute reusable platform components, reference architectures, and playbooks to the NewRocket Intelligence Platform, Data Intelligence Platform, and Agent Pack ecosystem. Build trusted working relationships across NewRocket engineering, delivery, product, AI, and client teams. Required Qualifications 5+ years of experience in platform engineering, cloud engineering, DevOps, software engineering, data engineering, systems integration, or related technical roles. Hands-on experience designing and deploying cloud-native applications and services on AWS, Microsoft Azure, and/or Google Cloud Platform. Strong experience with CI/CD, Git-based workflows, automated testing, infrastructure as code, and production release processes. Experience with containerization and orchestration technologies such as Docker, Kubernetes, serverless services, or comparable cloud-native platforms. Proficiency in Python, JavaScript/TypeScript, Java, Go, Bash, or similar programming and scripting languages. Experience designing and consuming REST APIs, integrating enterprise applications, and implementing authentication and authorization patterns. Hands-on experience with LLM-powered applications, generative AI services, AI/ML platforms, RAG systems, AI workflow automation, or related technologies. Familiarity with LLM application concepts, including prompt and context engineering, token management, embeddings, vector search, RAG, structured outputs, tool use/function calling, evaluations, and model monitoring. Experience with observability tools and practices, including logging, metrics, tracing, alerting, and incident management. Strong knowledge of cloud security, identity and access management, secrets management, network security, and secure software-development practices. Experience working with data systems such as relational databases, NoSQL databases, data warehouses, object storage, search platforms, or vector databases. Strong problem-solving, troubleshooting, communication, and documentation skills. Ability to work effectively in a fast-paced, collaborative, customer-oriented environment. Preferred Qualifications Anthropic & AI Platform Experience Hands-on experience with Claude, the Anthropic API, Anthropic Console, Claude Code, or Anthropic technical guidance. Completion of Anthropic Academy learning, partner enablement, technical training, or equivalent Claude implementation experience. Experience with Model Context Protocol (MCP), secure tool integrations, agent gateways, or comparable methods for connecting AI applications to enterprise systems. Experience with LLM application frameworks and orchestration tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, OpenAI Agents SDK, or comparable technologies. Experience implementing LLM evaluation, prompt/version management, AI tracing, guardrails, and AI observability platforms. Experience operating model gateways, API gateways, or AI-service routing layers. MLOps, Data & Cloud Engineering Experience with MLOps platforms and tools such as MLflow, SageMaker, Vertex AI, Azure Machine Learning, Databricks, Kubeflow, or comparable services. Experience with data engineering, ETL/ELT, streaming, data orchestration, data-quality testing, data governance, and data-catalog capabilities. Experience with vector databases and enterprise search technologies such as Pinecone, Weaviate, pgvector, OpenSearch, Elasticsearch, Azure AI Search, or similar platforms. Experience with Terraform, Pulumi, CloudFormation, Bicep, Helm, Argo CD, GitHub Actions, GitLab CI/CD, Azure DevOps, Jenkins, or comparable tooling. Experience with Kubernetes operations, service meshes, API management, event-driven architecture, and microservices. Familiarity with FinOps practices and optimization of cloud, model, inference, storage, and data-processing costs. ServiceNow & Enterprise Delivery Experience with ServiceNow architecture, development, integrations, platform operations, or workflow automation. Familiarity with ServiceNow APIs, IntegrationHub, Flow Designer, Virtual Agent, Now Assist, AI Agents, CMDB, knowledge management, and enterprise data-integration patterns. Experience working in consulting, professional services, enterprise architecture, or client-facing technical delivery environments. Education Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical discipline; equivalent relevant professional experience will be considered. Relevant certifications in cloud platforms, Kubernetes, DevOps, security, data engineering, ServiceNow, AI/ML, or Anthropic technologies are a plus. Why This Role Matters The AI Platform Engineer provides the technical backbone for NewRocket’s AI Foundry and Anthropic business. This role makes it possible for our teams and customers to move beyond isolated AI experiments and into secure, scalable, observable, and governed production solutions. By creating reusable platforms and engineering standards for Claude-powered AI, agentic workflows, enterprise data access, ServiceNow integrations, and responsible AI operations, you will help NewRocket deliver lasting business value—and scale trusted AI adoption across our clients. We Take Care of Our People NewRocket is committed to a diverse and inclusive workplace. We value and celebrate diversity, believing that every employee matters and should be respected and heard. We are proud to be an equal opportunity workplace and affirmative action employer, committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin, or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, citizenship, military, or Veteran status. For individuals with disabilities who would like to request an accommodation, please contact hr.us@newrocket.com.

Design, build, and maintain scalable infrastructure and platform capabilities for enterprise AI applications. | 5+ years in platform, cloud, or software engineering with expertise in cloud-native environments, AI/ML technologies, and programming in Python or JavaScript. | AI Platform Engineer-Anthropic AI Foundry | NewRocket Location: [Location / Hybrid / Remote] Travel based on client and business needs Reports to: Global AI Center of Excellence Lead / AI Platform Architect About NewRocket NewRocket is the AI-first Elite ServiceNow Partner that activates real value on the Now Platform. As a trusted advisor to enterprise leaders, we combine industry expertise, human-centered design, and enterprise-grade AI to help organizations navigate change and scale with confidence. With two decades of experience guiding clients to realize the full potential of the ServiceNow AI Platform, NewRocket is one of the largest pure-play ServiceNow partners. We are uniquely focused on enabling enterprises to adopt AI they trust—AI that delivers lasting business value. NewRocket is proud to be an Anthropic partner/vendor. Through this relationship, we are expanding our ability to help enterprise clients responsibly design, deploy, and scale AI solutions powered by Claude and other leading AI technologies. Our AI Foundry teams apply Anthropic-aligned practices across prompt and context engineering, retrieval-augmented generation (RAG), agentic workflows, tool use, structured outputs, model evaluation, security, governance, and human-in-the-loop controls. We #GoBeyondWorkflows to create new kinds of experiences for our customers. Come join our Crew! Role Overview NewRocket is seeking an experienced AI Platform Engineer to build, operate, and continuously improve the technical foundations that enable secure, reliable, scalable enterprise AI solutions. This role combines cloud engineering, platform engineering, DevOps, MLOps/LLMOps, data-platform integration, and applied AI engineering. The AI Platform Engineer will work closely with AI Architects, Forward Deployed AI Engineers, data engineers, ServiceNow teams, product engineering, and customer stakeholders to create reusable platforms, deployment patterns, controls, and operational capabilities for NewRocket’s Anthropic and enterprise AI business. You will help establish the infrastructure and engineering practices required to move AI solutions from prototype to governed production use. This includes enabling Claude and other LLM-powered applications; supporting RAG and agentic workflows; integrating enterprise data and tools; implementing observability and evaluation; and maintaining strong security, privacy, and governance controls. The ideal candidate is a hands-on engineer who is comfortable working across cloud infrastructure, APIs, CI/CD, data systems, containers, AI application frameworks, and enterprise security requirements. You are equally motivated by building reusable internal capabilities and solving practical customer-delivery challenges. Key Responsibilities AI Platform Architecture & Engineering Design, build, deploy, and maintain scalable platform capabilities that support enterprise AI, machine learning, LLM, RAG, and agentic AI applications. Create reusable reference architectures, infrastructure patterns, deployment templates, integration components, and engineering standards for NewRocket’s AI Foundry. Build platform capabilities that enable AI applications to securely connect to enterprise data, APIs, workflow systems, and authorized tools. Partner with AI Architects and Forward Deployed AI Engineers to translate client needs into reliable, supportable technical platform designs. Support the technical evolution of NewRocket’s AI intellectual property, including the NewRocket Intelligence Platform, Data Intelligence Platform, Value Realization Dashboard, Agent Packs, and reusable AI accelerators. Evaluate and recommend cloud, data, AI, observability, orchestration, and security technologies that improve delivery speed, quality, scalability, and cost efficiency. Anthropic, Claude & LLM Platform Enablement Build and maintain secure, reusable integrations with the Anthropic API, Claude models, and other approved AI services. Enable LLM-powered applications through standardized patterns for authentication, model access, prompt and context management, structured outputs, tool use, logging, error handling, and rate-limit management. Support Claude-based enterprise use cases involving document analysis, knowledge assistance, workflow automation, agentic task execution, summarization, classification, and decision support. Develop technical patterns for long-context workflows, document processing, RAG, structured data extraction, and model-driven automation. Support secure Model Context Protocol (MCP) and comparable tool-integration patterns that allow AI applications to access approved enterprise systems and data safely. Stay current on Anthropic platform capabilities, product releases, security guidance, technical enablement, and responsible AI practices. Complete relevant Anthropic partner training and enablement as available and help translate learning into reusable NewRocket engineering standards. LLMOps, MLOps & AI Operations Establish and operate CI/CD pipelines for AI applications, model configurations, prompts, evaluation assets, infrastructure, and integration services. Implement versioning, testing, release-management, rollback, and change-control practices for AI solutions. Build and maintain LLMOps and MLOps capabilities, including model/prompt configuration management, evaluation pipelines, deployment automation, monitoring, and lifecycle management. Develop automated evaluation and regression-testing frameworks to measure AI quality before and after releases. Support production operations for AI services, including incident response, troubleshooting, root-cause analysis, capacity planning, and service-level monitoring. Define and monitor operational metrics such as availability, latency, throughput, token consumption, model cost, tool-call success rates, task-completion rates, and error rates. Improve platform reliability, performance, resilience, and cost efficiency through automation, tuning, and operational improvements. Cloud Infrastructure, DevOps & Security Design and manage cloud infrastructure across AWS, Microsoft Azure, Google Cloud Platform, or client-approved environments. Build and maintain infrastructure using infrastructure-as-code tools such as Terraform, CloudFormation, Bicep, Pulumi, or comparable technologies. Implement containerized application and AI-service deployments using Docker, Kubernetes, serverless services, and cloud-native application patterns. Develop secure CI/CD workflows using Git-based source control, automated testing, artifact management, secrets management, and policy controls. Implement identity, access, and authentication patterns, including role-based access control, least-privilege access, API security, service accounts, and credential rotation. Partner with security, compliance, and client teams to ensure AI platforms align with enterprise security, privacy, regulatory, and data-residency requirements. Implement logging, monitoring, auditing, vulnerability management, disaster-recovery, and business-continuity practices for production AI services. Data Platform & RAG Enablement Build and support secure data-ingestion, transformation, indexing, and retrieval pipelines for enterprise AI applications. Design platform patterns for RAG, including document ingestion, parsing, chunking, metadata enrichment, embeddings, vector stores, hybrid search, retrieval, reranking, and source attribution. Integrate AI applications with structured and unstructured enterprise data sources, including databases, data warehouses, document repositories, knowledge bases, ServiceNow, and third-party SaaS platforms. Work with data engineers to establish data-quality, lineage, cataloging, permissions, retention, and governance practices that support trustworthy AI. Enable appropriate data-access controls so AI solutions retrieve and process only data the requesting user or service is authorized to access. Support data platforms and technologies such as Snowflake, Databricks, PostgreSQL, MongoDB, Elasticsearch/OpenSearch, vector databases, and cloud storage services, as appropriate. Responsible AI, Governance & Observability Implement technical controls that support responsible, secure, and governable AI deployments. Build safeguards for sensitive-data handling, data masking, content filtering, prompt injection, unsafe tool use, unauthorized access, and unintended agent behavior. Enable grounding, output validation, source attribution, confidence thresholds, fallback behavior, approval gates, and human-in-the-loop workflows. Implement AI observability and tracing across prompts, model calls, retrieval pipelines, tool execution, workflow outcomes, latency, errors, costs, and user feedback. Partner with AI Architects and governance stakeholders to document platform standards, risk controls, operating procedures, and solution limitations. Support auditability and compliance requirements through appropriate logging, retention, access reviews, and operational documentation. Enterprise Integration & ServiceNow Enablement Build and maintain integration patterns between AI platforms, ServiceNow, enterprise APIs, identity providers, workflow tools, collaboration platforms, and line-of-business systems. Support technical enablement for ServiceNow AI and workflow experiences, including IntegrationHub, Flow Designer, Virtual Agent, Now Assist, AI Agents, APIs, and knowledge-management capabilities where applicable. Develop secure APIs, middleware services, event-driven integrations, and automation components that support AI-enabled workflows. Collaborate with Forward Deployed AI Engineers to troubleshoot complex client integrations and transition successful engagement solutions into reusable platform components. Collaboration & Technical Leadership Work closely with AI Architects, AI/ML Engineers, Data Engineers, Product Engineering, ServiceNow developers, Business Process Consultants, and client technology teams. Provide technical guidance on AI platform engineering, cloud architecture, DevOps, LLMOps, data integration, performance, and security best practices. Contribute to internal playbooks, runbooks, reference architectures, technical documentation, reusable modules, and knowledge-sharing sessions. Identify recurring client requirements and convert them into scalable, productized platform features and accelerators. Participate in technical discovery, architecture reviews, demos, implementation planning, and customer workshops as needed. What Success Looks Like in the First 6 Months Establish or enhance reusable, secure deployment patterns for Claude-powered and other enterprise AI applications. Deliver reliable cloud, integration, data, and observability capabilities that support multiple AI Foundry client engagements. Implement CI/CD, infrastructure-as-code, monitoring, and LLMOps practices that improve deployment speed, quality, and operational maturity. Enable secure RAG, tool-use, and agentic AI patterns that integrate effectively with ServiceNow and enterprise ecosystems. Help productionize AI solutions through robust testing, evaluation, governance, access controls, and operational support practices. Contribute reusable platform components, reference architectures, and playbooks to the NewRocket Intelligence Platform, Data Intelligence Platform, and Agent Pack ecosystem. Build trusted working relationships across NewRocket engineering, delivery, product, AI, and client teams. Required Qualifications 5+ years of experience in platform engineering, cloud engineering, DevOps, software engineering, data engineering, systems integration, or related technical roles. Hands-on experience designing and deploying cloud-native applications and services on AWS, Microsoft Azure, and/or Google Cloud Platform. Strong experience with CI/CD, Git-based workflows, automated testing, infrastructure as code, and production release processes. Experience with containerization and orchestration technologies such as Docker, Kubernetes, serverless services, or comparable cloud-native platforms. Proficiency in Python, JavaScript/TypeScript, Java, Go, Bash, or similar programming and scripting languages. Experience designing and consuming REST APIs, integrating enterprise applications, and implementing authentication and authorization patterns. Hands-on experience with LLM-powered applications, generative AI services, AI/ML platforms, RAG systems, AI workflow automation, or related technologies. Familiarity with LLM application concepts, including prompt and context engineering, token management, embeddings, vector search, RAG, structured outputs, tool use/function calling, evaluations, and model monitoring. Experience with observability tools and practices, including logging, metrics, tracing, alerting, and incident management. Strong knowledge of cloud security, identity and access management, secrets management, network security, and secure software-development practices. Experience working with data systems such as relational databases, NoSQL databases, data warehouses, object storage, search platforms, or vector databases. Strong problem-solving, troubleshooting, communication, and documentation skills. Ability to work effectively in a fast-paced, collaborative, customer-oriented environment. Preferred Qualifications Anthropic & AI Platform Experience Hands-on experience with Claude, the Anthropic API, Anthropic Console, Claude Code, or Anthropic technical guidance. Completion of Anthropic Academy learning, partner enablement, technical training, or equivalent Claude implementation experience. Experience with Model Context Protocol (MCP), secure tool integrations, agent gateways, or comparable methods for connecting AI applications to enterprise systems. Experience with LLM application frameworks and orchestration tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, OpenAI Agents SDK, or comparable technologies. Experience implementing LLM evaluation, prompt/version management, AI tracing, guardrails, and AI observability platforms. Experience operating model gateways, API gateways, or AI-service routing layers. MLOps, Data & Cloud Engineering Experience with MLOps platforms and tools such as MLflow, SageMaker, Vertex AI, Azure Machine Learning, Databricks, Kubeflow, or comparable services. Experience with data engineering, ETL/ELT, streaming, data orchestration, data-quality testing, data governance, and data-catalog capabilities. Experience with vector databases and enterprise search technologies such as Pinecone, Weaviate, pgvector, OpenSearch, Elasticsearch, Azure AI Search, or similar platforms. Experience with Terraform, Pulumi, CloudFormation, Bicep, Helm, Argo CD, GitHub Actions, GitLab CI/CD, Azure DevOps, Jenkins, or comparable tooling. Experience with Kubernetes operations, service meshes, API management, event-driven architecture, and microservices. Familiarity with FinOps practices and optimization of cloud, model, inference, storage, and data-processing costs. ServiceNow & Enterprise Delivery Experience with ServiceNow architecture, development, integrations, platform operations, or workflow automation. Familiarity with ServiceNow APIs, IntegrationHub, Flow Designer, Virtual Agent, Now Assist, AI Agents, CMDB, knowledge management, and enterprise data-integration patterns. Experience working in consulting, professional services, enterprise architecture, or client-facing technical delivery environments. Education Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical discipline; equivalent relevant professional experience will be considered. Relevant certifications in cloud platforms, Kubernetes, DevOps, security, data engineering, ServiceNow, AI/ML, or Anthropic technologies are a plus. Why This Role Matters The AI Platform Engineer provides the technical backbone for NewRocket’s AI Foundry and Anthropic business. This role makes it possible for our teams and customers to move beyond isolated AI experiments and into secure, scalable, observable, and governed production solutions. By creating reusable platforms and engineering standards for Claude-powered AI, agentic workflows, enterprise data access, ServiceNow integrations, and responsible AI operations, you will help NewRocket deliver lasting business value—and scale trusted AI adoption across our clients.

Deploy and operationalize AI workflows and integrations in client environments collaborating with cross-functional teams. | 8+ years software engineering experience with proficiency in Python or JavaScript/TypeScript and hands-on LLM/cloud platform experience. | Senior Forward Deployed AI Engineer AI Foundry | NewRocket Location: Remote with travel (~25%) Role Overview NewRocket is seeking a highly skilled Senior Forward Deployed AI Engineer to join the AI Foundry team and work directly with customers to deploy, operationalize, and scale AI-powered workflow solutions. This role blends full-stack engineering, enterprise integration, generative AI implementation, and client-facing solution delivery. Forward Deployed AI Engineers partner closely with business consultants, product teams, AI/ML engineers, and customer stakeholders to translate real-world business problems into secure, reliable, deployable AI-driven solutions. As an Anthropic partner/vendor, NewRocket is expanding its capability to design and deliver enterprise solutions using Claude and other leading AI technologies. In this role, you will apply modern LLM engineering practices—including prompt and context engineering, retrieval-augmented generation (RAG), tool use, structured outputs, agentic workflows, model evaluation, and responsible AI controls—to deliver measurable customer value. You will help customers implement agentic AI workflows, intelligent automations, and AI-powered integrations within ServiceNow and broader enterprise ecosystems. You will also contribute directly to the evolution of NewRocket’s AI platforms, accelerators, and intellectual property, including the NewRocket Intelligence Platform, Value Realization Dashboard, Data Intelligence Platform, and reusable Agent Packs. This role requires strong engineering skills, curiosity about emerging AI technologies, sound judgment regarding responsible AI deployment, and the ability to operate effectively in fast-moving customer environments. Key Responsibilities Client Delivery & AI Solution Implementation Deploy, configure, and operationalize agentic AI workflows, AI assistants, and AI-powered automations within client ServiceNow environments and enterprise technology ecosystems. Translate customer business requirements, operational processes, and desired outcomes into technical architectures, implementation plans, and production-ready AI solutions. Implement and integrate NewRocket Agent Packs, AI accelerators, and workflow solutions into enterprise environments. Work directly with customer teams to tailor AI solutions to their operating models, business processes, data sources, security requirements, and user needs. Support workshops, discovery sessions, technical working sessions, demonstrations, pilots, and production rollouts. Clearly communicate AI capabilities, limitations, tradeoffs, solution behavior, and adoption considerations to technical and business stakeholders. Anthropic and Generative AI Engineering Build enterprise AI applications and workflows using Claude, the Anthropic API, and other LLM platforms as appropriate for the client use case. Apply effective prompt and context-engineering techniques, including clear instructions, examples, role and task definition, structured inputs, response constraints, and long-context management. Design and implement AI workflows using structured outputs, tool use/function calling, API integrations, multi-step orchestration, and human-in-the-loop review patterns. Build retrieval-augmented generation (RAG) solutions that ground AI responses in authorized enterprise data and knowledge sources. Implement practical techniques to improve reliability and user trust, including citation or source-grounding patterns, validation, confidence thresholds, output schemas, fallback handling, and escalation workflows. Stay current on Anthropic platform capabilities, Claude model releases, implementation guidance, responsible AI principles, and enterprise deployment best practices. Complete relevant Anthropic training, partner enablement, and technical education programs as available, and incorporate those practices into NewRocket solution delivery. Solution Engineering & Prototyping Build demos, prototypes, and proof-of-concept implementations that validate AI-driven workflows and customer use cases. Rapidly iterate with customers and internal teams to refine AI-powered solutions based on feedback, performance results, and operational needs. Support the design and implementation of AI orchestration, LLM integrations, agentic decision models, and workflow automation patterns. Evaluate when an agentic approach is appropriate versus deterministic automation, traditional workflow logic, search, analytics, or human review. Develop reusable implementation patterns, solution templates, prompt libraries, integrations, and deployment assets that accelerate future client delivery. Full-Stack Engineering & Integration Develop secure integrations between ServiceNow, enterprise systems, APIs, data platforms, and AI services. Build supporting components such as scripts, microservices, automation logic, integration services, and lightweight user interfaces. Implement integrations with AI platforms, enterprise APIs, identity systems, document repositories, databases, and structured and unstructured data sources. Apply sound engineering practices for authentication, authorization, secrets management, access controls, logging, error handling, version control, and documentation. Design solutions that meet enterprise expectations for security, scalability, maintainability, observability, and production readiness. AI Quality, Evaluation & Responsible AI Develop and execute practical evaluation approaches for AI applications, including test cases, representative datasets, success metrics, and regression testing. Assess AI workflow quality across dimensions such as relevance, accuracy, groundedness, task completion, safety, latency, cost, and user experience. Implement safeguards for sensitive data, role-based permissions, appropriate data access, prompt injection risks, unsafe tool use, and unintended model behavior. Establish human-in-the-loop workflows for sensitive, high-impact, low-confidence, or exception-based decisions. Document AI solution behavior, known limitations, risk controls, governance considerations, and operational support procedures. Monitor and improve deployed solutions based on user feedback, usage patterns, performance data, incidents, and evolving customer needs. Product & Platform Contribution Actively contribute to the development and evolution of NewRocket’s AI intellectual property and platforms, including: NewRocket Intelligence Platform Value Realization Dashboard Data Intelligence Platform Agent Packs and reusable AI solution accelerators Responsibilities include: Identifying common patterns, requirements, integration needs, and capabilities discovered through customer deployments. Contributing reusable assets, integration components, prompt patterns, evaluation frameworks, and automation capabilities. Providing actionable product feedback that improves usability, reliability, scalability, security, and customer value. Helping transform successful client implementations into repeatable platform features, accelerators, and delivery playbooks. Supporting the definition of standards and best practices for enterprise AI delivery across NewRocket’s AI Foundry. Systems Integration & Troubleshooting Diagnose and resolve technical issues across AI workflows, integrations, retrieval pipelines, data connections, and automation processes. Troubleshoot issues related to model inputs and outputs, prompt behavior, tool execution, API reliability, permissions, data quality, and system performance. Ensure deployed AI solutions are secure, scalable, supportable, and production-ready. Optimize deployed systems for reliability, performance, latency, model usage, and cost efficiency. Cross-Team Collaboration Work closely with Business Process Consultants, Product Engineering, Data Engineers, AI/ML Engineers, ServiceNow teams, and the AI Center of Excellence. Serve as the engineering counterpart to consulting and delivery teams throughout discovery, solution design, implementation, rollout, and continuous improvement. Contribute to internal playbooks, technical documentation, reusable deployment patterns, reference architectures, and product evolution. Share lessons learned from customer deployments to strengthen NewRocket’s AI delivery capabilities and solution portfolio. What Success Looks Like in the First 6 Months Successfully deploy AI-powered workflows, assistants, automations, or integrations across multiple customer engagements. Deliver secure, reliable AI workflows within customer ServiceNow environments and connected enterprise systems. Build trusted relationships with customer technical teams, business stakeholders, and NewRocket delivery teams. Demonstrate strong practical application of Claude and modern LLM engineering practices, including prompt/context engineering, tool use, RAG, evaluations, and responsible AI controls. Contribute reusable components, implementation patterns, prompt assets, and improvements to NewRocket’s AI platforms and accelerators. Provide actionable customer-driven feedback that improves the NewRocket Intelligence Platform and related products. Help establish repeatable methods for moving AI use cases from prototype through governed production deployment. Required Qualifications 8+ years of experience in software engineering, systems integration, enterprise platforms, workflow automation, or related technical delivery roles. Strong engineering foundation, with hands-on experience in full-stack development, scripting, APIs, microservices, enterprise integrations, or cloud-native applications. Experience building, deploying, or supporting AI/LLM-powered applications, AI-enabled automations, conversational experiences, RAG systems, or agentic workflows. Experience integrating APIs, enterprise applications, data platforms, or workflow systems in production environments. Proficiency in JavaScript/TypeScript, Python, or similar programming and scripting languages. Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud. Familiarity with modern LLM application concepts, including prompt engineering, context windows, token usage, embeddings, vector search, RAG, tool use/function calling, structured outputs, and model evaluation. Understanding of responsible AI concepts, including hallucination mitigation, sensitive-data handling, identity and access controls, human oversight, AI safety, and secure AI deployment. Experience operating in customer-facing engineering, consulting, technical implementation, solutions architecture, or professional-services roles. Strong problem-solving skills and the ability to communicate complex technical concepts clearly to both technical and business stakeholders. Ability to manage ambiguity, prioritize effectively, travel approximately 25%, and deliver high-quality solutions in fast-moving customer environments. Preferred Qualifications Anthropic / Claude Experience Hands-on experience with the Anthropic API, Claude models, Anthropic Console, Claude Code, or Anthropic implementation guidance. Completion of relevant Anthropic Academy learning, partner enablement, technical training, or equivalent hands-on experience deploying Claude-based solutions. Experience applying Claude capabilities such as long-context processing, tool use, structured outputs, document analysis, and enterprise knowledge workflows. Familiarity with Model Context Protocol (MCP) concepts and experience building or integrating secure tools and data connections for AI applications. ServiceNow Experience — Strong Plus Experience with ServiceNow development, configuration, workflow automation, or enterprise platform implementation. Familiarity with ServiceNow scripting, APIs, IntegrationHub, Flow Designer, Virtual Agent, Now Assist, AI Agents, and platform development patterns. Understanding of ServiceNow data models and enterprise workflow concepts, including: CMDB ITSM, CSM, HRSD, or employee workflows Workflow and task tables Knowledge management Enterprise integrations and data exchange patterns AI, Data & Platform Experience Experience building AI prototypes, RAG systems, semantic search capabilities, AI assistants, or agent-based workflows. Experience integrating LLM APIs or AI services into enterprise applications and business processes. Experience with vector databases, embeddings, document ingestion, chunking, retrieval strategies, and knowledge-grounding patterns. Familiarity with LLM orchestration and application frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or comparable tools. Experience with AI observability, tracing, evaluation frameworks, prompt/version management, monitoring, and cost optimization. Experience contributing to internal platforms, reusable accelerators, developer tooling, or product capabilities. Familiarity with Docker, CI/CD, SQL, Git, infrastructure-as-code, and secure cloud deployment practices. Why This Role Matters Forward Deployed AI Engineers are the bridge between real-world enterprise problems and NewRocket’s AI platforms. By working directly with customers, they deliver immediate operational value while shaping the evolution of NewRocket’s AI products, accelerators, and platform capabilities. This role is critical to scaling the NewRocket Intelligence Platform and the broader AI Foundry strategy. As NewRocket expands its partnership with Anthropic, this engineer will help establish practical, secure, and responsible patterns for deploying Claude-powered AI solutions that improve enterprise workflows, accelerate decision-making, and create measurable business outcomes. We Take Care of Our People NewRocket is committed to a diverse and inclusive workplace. We value and celebrate diversity, believing that every employee matters and should be respected and heard. We are proud to be an equal opportunity workplace and affirmative action employer, committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin, or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, citizenship, military, or Veteran status. For individuals with disabilities who would like to request an accommodation, please contact hr.us@newrocket.com.

Design and implement dynamic Service Portal solutions on ServiceNow platform managing full application lifecycle. | Requires 5+ years ServiceNow development experience, front-end proficiency, bachelor's degree, and ServiceNow certifications. | NewRocket brings 20 years of advising and supporting clients in designing, implementing, and managing AI-enabled digital workflows to improve employee and customer experiences. An Elite ServiceNow Partner and ServiceNow Global Partner Award Winner, the Company has completed over 3,000 projects across nine industry specializations. NewRocket Goes Beyond Workflows™ to help clients transform their enterprise into a place where employees flourish, customers thrive, and people matter. With thousands of ServiceNow certifications, NewRocket's business strategists take a holistic, strategic approach to optimize the ServiceNow platform and help clients solve industry-specific challenges. NewRocket has been awarded the “2024 BEST Award”, “2024 ServiceNow Customer & Industry Workflows Delivery Success Partner (CIWF)”, “2023 ServiceNow Worldwide Customer Workflow Partner of the Year” and “2023 ServiceNow Creator Workflow Partner of the Year”. We are #GoingBeyond Come join our Crew! Our Approach to Work At NewRocket, people are not just the backbone; they're the heartbeat. We champion diversity, celebrate creativity, and embrace the uniqueness each person brings to the table. Here, it's not just about a job; it's about fostering a healthy work-life balance, creating a culture that thrives on collaboration and innovation, and supporting professional growth for individuals and teams. We believe in creating meaningful experiences, not just for our clients but for every member of our crew. Your voice matters, your growth matters, and you matter. Join us for a journey where your uniqueness is not only recognized but celebrated, and together, let's create something extraordinary! Your Career We are looking for a rockstar Solution Architect, who excels in the Service Portal space on the ServiceNow platform. As a Service Portal Architect, you are excited about building great user experiences, with new front-end technologies, and ready to #RaiseTheBar on what is achievable. You will implement dynamic and responsive Service Portal solutions and end user interfaces on the ServiceNow platform. If you are curious, look for challenges and opportunities and have the desire to bring new ideas to our customer solutions – then this position is for you! You will have the opportunity to refine the standard for Service Portal implementations and evolve the technology stack to build modern and awesome user experiences for our customers. Your Impact Create mobile and web applications based on site maps, wireframes and visual designs using standards compliant JavaScript, HTML5 and CSS3. Manage all aspects of application development, including design, coding, debugging, testing, troubleshooting, and documenting systems, query optimization, and report-writing. Design and customize Service Portal ServiceNow applications or product based solutions based on ServiceNow applications. Implements integrations with ServiceNow Discovery and Core module (Normal Incident, MIM, Problem, Knowledge, Change, ESS, CMS ). Creation of script-based Assignment and Approval rules, custom-related lists, Access Control list, UI Policy, and client script. Create and execute development plans as appropriate to meet changing needs and requirements. Understands ITIL V3 processes and is hands-on with ITIL process implementation. Conduct requirements gathering workshops for customers Help integration team in planning and packaging the ServiceNow service portal integration solution. Draft use cases and functional requirements documents. Draft proposals and statements of work for solutions. Reviewing and providing guidance on functional requirements documents. Provide technical assistance in a pre-sale’s capacity. Your Experience 5+ years of ServiceNow Platform experience, with an in-depth understanding of ServiceNow architecture. 5+ years of experience in application development at a SaaS, PaaS, or Enterprise Software Development Company, preferably ServiceNow. Solid understanding of building performant and scalable user interfaces with large scale data, an obsession with design aesthetics, and engineering excellence. Experience with ServiceNow Service Portal (HTML, CSS, AngularJS, SASS, Bootstrap). ServiceNow Application Development (Scoped Applications) experience. 3rd Party Integrations Development (REST, SOAP, MID Servers, etc) experience. Understanding of object-oriented and relational database design. Experience interacting with REST APIs. Exposure and proficiency with HTML, CSS and JS. Exposure and understanding of design patterns. Passion in engineering science and technology. Excels in applying principles, techniques, procedures, and equipment to the design and production of managed services. Collaboration with customers is something you love to do! Including customer needs assessment, meeting quality standards for services, and evaluation of customer satisfaction. Thrives in strategic planning, resource allocation, production methods, and coordination of people and resources. Knowledge of ITIL V3 processes and hands-on with ITIL process implementation. Certifications & Knowledge A four-year undergraduate degree in Computer Science, Computer Engineering, Information Systems, or demonstrated working experience ServiceNow Certified System Administrator or relevant experience ServiceNow Certified Application Developer or relevant experience ServiceNow Certified Implementation Specialist in two or more applications The candidate must be willing and able to continue their education within the ServiceNow platform and beyond. It is expected that the candidate will be able to complete ServiceNow competency Certifications as well as Module Accreditations. We Take Care of Our People NewRocket is committed to a diverse and inclusive workplace. We value and celebrate diversity, believing that every employee matters and should be respected and heard. We are proud to be an equal opportunity workplace and affirmative action employer, committed to providing employment opportunity regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin, or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, citizenship, military, or Veteran status For individuals with disabilities who would like to request an accommodation, please contact hr.us@NewRocket.com.