LTS

Design and implement AI capabilities to improve reasoning and productivity in production systems. | Bachelor's degree and 5+ years in software engineering or applied AI with proficiency in Python and LLM-related technologies. | Location: United States – Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a highly skilled Senior Applied AI Engineer to focus on continuously improving the intelligence behind the platform. You'll experiment with models, optimize retrieval strategies, refine agent reasoning, evaluate AI performance, and transform emerging AI capabilities into production-ready solutions. The Agentic AI platform is designed to help engineers understand, analyze, and modernize one of the most consequential legacy software systems still operating today. Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to decades of production source code. Rather than replacing engineers, we're building AI that accelerates engineering through transparency, traceability, and intelligent reasoning. We're building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide. The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements. The platform has executive sponsorship, committed users, and a customer investing in long-term modernization. Our engineering team is intentionally small giving every engineer meaningful ownership, and direct influence over product direction. We don't simply build AI-powered software—we build software with AI. This is not another chatbot. Using LLMs, autonomous agents, AI-assisted development, parallel workflows, and model-driven engineering is simply how we work. What You’ll Do: Advance Applied AI Capabilities Design, prototype, and implement production-ready AI capabilities that improve reasoning, accuracy, explainability, and developer productivity. Evaluate emerging LLMs, multimodal models, agent frameworks, and AI techniques to identify opportunities for platform advancement. Rapidly prototype new AI capabilities and transition successful experiments into production. Optimize Agent Performance Improve autonomous and multi-agent workflows through prompt engineering, reasoning optimization, memory strategies, tool selection, and context management. Continuously refine Retrieval-Augmented Generation (RAG) pipelines, retrieval strategies, embeddings, reranking, and grounding techniques. Improve AI response quality through experimentation, benchmarking, and iterative optimization. Evaluate AI Systems Develop evaluation frameworks that measure accuracy, groundedness, explainability, latency, and overall AI effectiveness. Build benchmark datasets, automated evaluation pipelines, and performance metrics for production AI systems. Analyze AI failures, hallucinations, retrieval gaps, and reasoning errors to drive continuous improvement. Knowledge Engineer Collaborate with software engineers to improve knowledge ingestion, document processing, semantic search, embeddings, and enterprise knowledge management. Design approaches that maximize retrieval quality across large technical documentation and source code repositories. Improve how AI agents discover, organize, and reason over enterprise knowledge. Collaborate Across Engineer Partner closely with AI architects, platform engineers, software engineers, and front-end engineers to improve the overall intelligence of the platform. Share research findings, experimental results, and engineering recommendations with cross-functional teams. Help establish best practices for experimentation, evaluation, and AI quality throughout the organization. What We’re Looking For: Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Engineering, Data Science, or a related technical discipline (or equivalent professional experience). 5+ years of software engineering, applied AI, machine learning, or AI systems development experience. Demonstrated experience developing production AI applications powered by Large Language Models (LLMs). Experience designing and optimizing Retrieval-Augmented Generation (RAG) systems. Experience with prompt engineering, embeddings, semantic search, vector databases, and knowledge retrieval. Experience evaluating AI model performance and implementing experimentation frameworks. Strong programming skills in Python and experience with modern software engineering practices. Experience with AI frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar. Experience with using AI coding assistants as part of your daily workflow. Familiarity with REST APIs, cloud-native applications, and distributed software systems. Strong analytical, problem-solving, and communication skills. Intellect and curiosity for AI systems and how they behave. Deep passion for experimenting with new AI techniques. Background in evaluation, explainability, and continuous improvement. Proven success with ownership of difficult technical challenges and collaboration across disciplines. Nice to Have: Experience optimizing autonomous or multi-agent AI systems. Experience implementing automated AI evaluation frameworks. Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Vertex AI, AWS Bedrock, or open-source LLMs. Experience with vector databases including Pinecone, Weaviate, Qdrant, Milvus, or Azure AI Search. Experience with Responsible AI, AI governance, safety, and explainability. Familiarity with software engineering tools, code intelligence platforms, or developer productivity solutions. Experience supporting healthcare, Federal Government, or other highly regulated environments. Experience using AI coding assistants and autonomous agents as part of daily software development. What’s In It for You? The Opportunity to support high-visibility federal missions A culture that values innovation, growth, and collaboration Access to cutting-edge tools and technologies Comprehensive benefits for you and your family A career path that rewards ambition and performance If you’re ready to push boundaries, sharpen your skills, and join a team that is passionate about building what’s next, we’d love to meet you. Apply today and let’s build a future together! LTS shares salary ranges to promote transparency. Compensation ranges are provided for informational purposes, and final compensation may vary based on experience, skills, location, and role requirements. LTS is committed to offering eligible employees comprehensive benefits that will provide them with options intended to meet their needs and the needs of their family.

Design and implement security controls for autonomous AI systems, perform threat modeling, and build observability mechanisms to ensure AI system security and compliance. | Bachelor's degree with 7+ years in software engineering, cybersecurity, or AI development, strong Python or TypeScript skills, and deep understanding of AI security risks and cloud architectures. | Location: United States – Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a highly skilled Agentic AI Security Engineer to ensure our AI systems are secure, trustworthy, resilient, and governed responsibly. You'll design safeguards that protect AI agents, retrieval pipelines, prompts, tools, memory, and model interactions from misuse while ensuring every AI response remains explainable, auditable, and aligned with enterprise security and compliance requirements. This role focuses on securing AI systems, not simply securing infrastructure. The Agentic AI platform is designed to help engineers understand, analyze, and modernize one of the most consequential legacy software systems still operating today. Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to decades of production source code. Rather than replacing engineers, we're building AI that accelerates engineering through transparency, traceability, and intelligent reasoning. We're building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide. The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements. You'll work alongside AI architects, software engineers, platform engineers, cybersecurity engineers, and product leaders to embed AI security into every stage of development from experimentation through production deployment. We’re building an AI platform where security, transparency, and trust are foundational, not afterthoughts. What You’ll Do: Secure Agentic AI Systems Design and implement security controls for autonomous and multi-agent AI systems. Secure agent orchestration, tool execution, memory, and external integrations. Identify and mitigate emerging AI-specific attack vectors and vulnerabilities. Protect AI Models and Knowledge Systems Secure Retrieval-Augmented Generation (RAG) pipelines, embeddings, vector databases, and enterprise knowledge repositories. Design controls that prevent unauthorized knowledge access, data leakage, and information exposure. Implement secure handling of sensitive enterprise and healthcare data throughout AI workflows. AI Threat Modeling Perform threat modeling for AI applications, agent architectures, prompts, APIs, and retrieval systems. Assess risks associated with prompt injection, jailbreak attempts, indirect prompt attacks, tool misuse, hallucinations, data poisoning, model abuse, and adversarial inputs. Develop mitigation strategies that reduce AI-specific security risks while maintaining usability. Responsible AI & Governance Build guardrails that improve trustworthy AI behavior. Design policy enforcement, human-in-the-loop approval workflows, content filtering, and AI governance mechanisms. Help define organizational standards for responsible AI development and deployment. AI Observability & Monitoring Design monitoring capabilities that detect abnormal agent behavior, misuse, prompt manipulation, and anomalous model interactions. Implement logging, traceability, and audit capabilities supporting explainability and regulatory compliance. Build mechanisms for continuous AI risk assessment and operational visibility. Secure AI Development Partner with software engineers to integrate AI security into development workflows. Conduct security reviews of AI features before production deployment. Promote secure AI engineering practices across the product organization. What We’re Looking For: Bachelor's degree in Computer Science, Cybersecurity, Artificial Intelligence, Software Engineering, Information Security, or a related technical discipline (or equivalent professional experience). 7+ years of software engineering, cybersecurity engineering, AI engineering, or application security experience. Experience designing secure cloud-native or distributed software systems. Experience with Large Language Models (LLMs), AI applications, or Agentic AI platforms. Experience securing APIs, microservices, and enterprise applications. Knowledge of OWASP Top 10 and secure software development practices. Understanding of AI-specific security risks including: Prompt injection Jailbreaking Data poisoning Model abuse Adversarial inputs Hallucination mitigation Sensitive data leakage Experience with cloud security across AWS, Azure, or Google Cloud. Strong programming experience in Python or TypeScript. Excellent communication and collaboration skills. A mindset of both a security engineer and a software engineer. Experience with solving problems that don’t yet have established playbooks. Ability to stay current with emerging AI threats and defensive techniques. Experience with ownership of complex technical challenges. Ability to collaborate effectively across engineering disciplines. Capability to influence how secure AI systems are built in highly regulated environments. Strong ability to balance innovation with responsible engineering. Nice to Have: Experience securing Retrieval-Augmented Generation (RAG) systems. Experience with AI guardrails and policy engines. Familiarity with frameworks such as LangGraph, LangChain, CrewAI, Semantic Kernel, AutoGen, or LlamaIndex. Experience with vector databases including Pinecone, Weaviate, Qdrant, Milvus, or Azure AI Search. Experience implementing AI observability, evaluation, or monitoring solutions. Experience with NIST AI Risk Management Framework (AI RMF), Responsible AI practices, or AI governance frameworks. Experience supporting Federal Government or healthcare environments. Familiarity with Zero Trust Architecture and secure DevSecOps practices. Professional certifications such as CISSP, CCSP, Security+, GIAC, or cloud security certifications are a plus. What’s In It for You? The Opportunity to support high-visibility federal missions A culture that values innovation, growth, and collaboration Access to cutting-edge tools and technologies Comprehensive benefits for you and your family A career path that rewards ambition and performance If you’re ready to push boundaries, sharpen your skills, and join a team that is passionate about building what’s next, we’d love to meet you. Apply today and let’s build a future together! LTS shares salary ranges to promote transparency. Compensation ranges are provided for informational purposes, and final compensation may vary based on experience, skills, location, and role requirements. LTS is committed to offering eligible employees comprehensive benefits that will provide them with options intended to meet their needs and the needs of their family.

Design and own the end-to-end front-end experience for an enterprise-scale Agentic AI platform with real-time, interactive interfaces. | 7+ years front-end experience with expert React and TypeScript skills and a bachelor's degree in a related field. | United States – Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a Senior Front-End Agentic AI Engineer to own the experience layer of an AI platform built for one of the most consequential legacy systems still running in production today. Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to the exact lines of source code. Rather than replacing engineers, we're building AI that helps them understand decades of complex software faster, with complete transparency and confidence. We're building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide. Every response generated by the platform must be explainable, traceable, and trustworthy. The front end is where that trust is earned. The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements. When an engineer asks a question about a decades-old codebase, your interface determines whether they trust the answer or close the tab. You'll own that experience from end to end. The product has executive sponsorship, committed users, a clearly defined mission, and a customer who knows exactly what success looks like. Our engineering team is intentionally small. Every engineer has significant ownership, meaningful influence over product direction, and the opportunity to help define how engineers interact with AI. We don't simply build AI-powered software—we build software with AI. This is not another chatbot. Using AI agents, LLMs, parallel workflows, and model-assisted development is simply how we engineer. What You’ll Do: Own the end-to-end front-end experience for an enterprise-scale Agentic AI platform. Design intuitive interfaces that transform complex AI reasoning into experiences engineers’ trust. Build and maintain conversational interfaces, embedded AI assistants, review workflows, and authoring experiences using React, TypeScript, and modern front-end technologies. Develop the rendering pipeline for streaming AI responses, markdown, source citations, code blocks, dependency graphs, workflow visualizations, and technical documentation. Build evidence and traceability experiences that allow users to validate AI-generated answers by navigating directly to source code, documentation, and supporting artifacts. Design interaction patterns for agentic workflows, including multi-step reasoning, tool execution, progress visualization, human-in-the-loop review, and long-running AI tasks. Build responsive real-time user experiences using WebSockets, streaming APIs, and modern state management patterns. Partner closely with AI engineers to define how agent output is translated into intuitive user experiences. Collaborate with product managers, UX designers, architects, and platform engineers to rapidly prototype, validate, and deliver new capabilities. Build scalable component libraries and reusable design systems supporting future platform growth. Optimize performance, accessibility, responsiveness, and usability across enterprise environments, including Section 508 compliance. Instrument the application with analytics, observability, and client-side monitoring to continuously improve user experience. Use AI-native engineering workflows to accelerate development, improve software quality, and increase engineering velocity. What We’re Looking For: Bachelor's degree in Computer Science, Software Engineering, or related discipline (or equivalent professional experience). 7+ years of professional front-end software engineering experience building production web applications. Expert-level proficiency with React, TypeScript, modern JavaScript, and contemporary front-end architecture. Experience building highly interactive, data-rich user interfaces. Strong understanding of component architecture, state management, and scalable front-end engineering. Experience building real-time user experiences using streaming APIs, WebSockets, or Server-Sent Events. Experience consuming complex REST, GraphQL, tRPC, or comparable typed APIs. Experience collaborating closely with backend engineers, designers, and product teams in Agile environments. Excellent communication skills and the ability to explain technical decisions clearly across engineering and business stakeholders. Mindset of a product engineer rather than a feature developer. Engineers capable of building software from first principles. Passion for usability, interaction design, and developer experience. Strong ability to carefully analyze requirements before writing code. Preference for ownership over narrowly defined responsibilities. Experience operating across the client/server boundary when necessary. Expertise using AI coding assistants, parallel agents, and model-driven development workflows. Efficiency while maintaining high engineering standards. Innate ability to solve difficult engineering problems that don't have obvious solutions. Nice to Have: Experience in healthcare, regulated industries, or large-scale enterprise modernization programs is a plus. Experience building AI-native products, LLM-powered applications, or agentic AI systems. Experience designing interfaces for AI assistants, copilots, developer tools, or knowledge platforms. Familiarity with Retrieval-Augmented Generation (RAG), vector search, embeddings, or agent orchestration frameworks. Experience rendering complex technical content including markdown, syntax highlighting, dependency graphs, diagrams, or code relationships. Experience developing products for software engineers or other highly technical users. Experience with cloud-native platforms including AWS or Azure. Experience building design systems or reusable component libraries. Familiarity with accessibility standards including Section 508 and WCAG. Experience using AI coding assistants and parallel AI workflows as part of daily software development. Why Join LTS? At LTS, we support impactful programs that directly improve healthcare services for Veterans nationwide. Our teams work on innovative modernization initiatives that help transform legacy systems into secure, scalable, and mission-focused digital solutions. We value collaboration, integrity, and professional growth while empowering employees to contribute to meaningful federal healthcare missions. LTS shares salary ranges to promote transparency. Compensation ranges are provided for informational purposes, and final compensation may vary based on experience, skills, location, and role requirements. LTS is committed to offering eligible employees comprehensive benefits that will provide them with options intended to meet their needs and the needs of their family.

Design and develop autonomous multi-agent AI systems and orchestration pipelines to modernize legacy software. | Bachelor's degree, 7+ years software engineering, 3+ years AI production experience, strong Python and distributed systems skills. | Location: United States – Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a Senior Agentic AI Software Engineer to build the intelligence behind the platform—the autonomous agents, orchestration layers, retrieval pipelines, reasoning workflows, and backend services that transform complex legacy software into actionable engineering knowledge. The Agentic AI platform is designed to help engineers understand, analyze, and modernize one of the most consequential legacy software systems still operating today. Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to decades of production source code. Rather than replacing engineers, we're building AI that accelerates engineering through transparency, traceability, and intelligent reasoning. We're building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide. Every response generated by the platform must be explainable, grounded in evidence, and trusted by engineers responsible for maintaining software that millions of people quietly depend on every day. The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements. The product has executive sponsorship, committed users, and a customer investing in long-term modernization. Our engineering team is intentionally small. Every engineer has meaningful ownership, significant technical influence, and the opportunity to help define how AI transforms software engineering. We don't simply build AI-powered software—we build software with AI. This is not another chatbot. Using LLMs, autonomous agents, AI-assisted development, parallel workflows, and model-driven engineering is simply how we work. What You’ll Do: Build Intelligent Agentic Systems Design, develop, and deploy autonomous and multi-agent AI systems capable of reasoning, planning, tool use, workflow automation, and human-in-the-loop collaboration. Build intelligent orchestration pipelines coordinating LLMs, specialized agents, enterprise tools, and structured reasoning workflows. Develop reusable agent architectures and orchestration patterns that accelerate intelligent application development across the platform. Engineer Enterprise Retrieval & Knowledge Systems Design and optimize Retrieval-Augmented Generation (RAG) pipelines including document ingestion, embeddings, hybrid retrieval, reranking, semantic search, context engineering, and prompt orchestration. Integrate AI systems with source code repositories, enterprise documentation, APIs, structured data, and knowledge repositories. Ensure every AI-generated response is explainable, evidence-based, and traceable to authoritative sources. Build Production Software Design and implement scalable backend services, APIs, and cloud-native applications supporting enterprise AI workloads. Develop distributed systems capable of serving low-latency AI experiences while maintaining security, reliability, and observability. Optimize performance, latency, throughput, model quality, and infrastructure cost across production AI systems. Deliver Reliable AI Implement testing, evaluation, monitoring, observability, guardrails, and LLMOps practices to ensure AI systems remain trustworthy and production-ready. Continuously evaluate emerging models, frameworks, and engineering practices to improve platform capabilities. Build AI systems that behave predictably in highly regulated enterprise environments. Collaborate Across the Product Team Partner closely with AI architects, platform engineers, front-end engineers, designers, and product leaders to deliver cohesive AI-powered experiences. Mentor engineers through technical leadership, architecture discussions, design reviews, and collaborative problem solving. Help establish engineering standards, reusable frameworks, and best practices across the AI engineering organization. What We’re Looking For: Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Engineering, or a related technical discipline (or equivalent professional experience). 7+ years of professional software engineering experience designing and building distributed production systems. At least 3 years designing, developing, and deploying production AI applications beyond proof-of-concept environments. Strong proficiency in Python and modern backend software engineering. Experience building enterprise APIs, microservices, and cloud-native applications. Hands-on experience developing applications powered by Large Language Models (LLMs) and Generative AI. Experience building Agentic AI solutions using frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or comparable technologies. Strong experience designing Retrieval-Augmented Generation (RAG) architectures including embeddings, vector search, hybrid retrieval, reranking, context engineering, and grounding techniques. Experience integrating AI systems with enterprise APIs, databases, cloud platforms, and business applications. Experience with Docker, Kubernetes, Git, CI/CD pipelines, and modern DevOps practices. Strong understanding of software architecture, testing, observability, debugging, and production operations. Excellent communication skills with the ability to explain complex technical concepts to both engineering and business stakeholders. Ability to solve difficult engineering problems from first principles. Ability to think deeply about system architecture, reliability, and scalability. Passionate about explainability as model performance. Ability to move comfortably between distributed systems, AI frameworks, and product engineering. Willingness to take ownership of ambiguous, high-impact technical challenges. Background with using AI coding assistants, autonomous agents, and model-driven engineering workflows. A technically skilled engineer with a preference for building products that create lasting impact over incremental feature development. Nice to Have: Experience developing multi-agent AI systems and collaborative agent workflows. Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Vertex AI, AWS Bedrock, or open-source LLMs. Experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or Azure AI Search. Experience implementing LLMOps or MLOps practices. Familiarity with graph databases, knowledge graphs, or dependency analysis. Experience working with software engineering tools, code intelligence platforms, or developer productivity products. Experience building AI systems in healthcare, Federal Government, or other highly regulated environments. Familiarity with Responsible AI, AI governance, privacy, security, and compliance best practices. Experience using AI coding assistants and autonomous agents as part of daily software development. What’s In It for You? The Opportunity to support high-visibility federal missions A culture that values innovation, growth, and collaboration Access to cutting-edge tools and technologies Comprehensive benefits for you and your family A career path that rewards ambition and performance If you’re ready to push boundaries, sharpen your skills, and join a team that is passionate about building what’s next, we’d love to meet you. Apply today and let’s build a future together! LTS shares salary ranges to promote transparency. Compensation ranges are provided for informational purposes, and final compensation may vary based on experience, skills, location, and role requirements. LTS is committed to offering eligible employees comprehensive benefits that will provide them with options intended to meet their needs and the needs of their family.

Design and build secure identity architectures and implement authentication and authorization frameworks for AI and enterprise platforms. | 7+ years in software or identity engineering with strong knowledge of OAuth 2.0, OIDC, cloud-native architectures, and a technical bachelor's degree. | Location: United States - Remote Clearance: Ability to obtain and maintain a Public Trust LTS is seeking a Senior AI Identity Platform Engineer to design and build the identity foundation that enables AI agents, enterprise applications, cloud services, and users to interact securely and intelligently. You'll establish authentication, authorization, credential management, and identity services that allow autonomous AI systems to operate safely across enterprise environments. The Agentic AI platform is designed to help engineers understand, analyze, and modernize one of the most consequential legacy software systems still operating today. Our platform enables engineers to ask questions in plain English and receive explainable, verifiable answers traced directly back to decades of production source code. Rather than replacing engineers, we're building AI that accelerates engineering through transparency, traceability, and intelligent reasoning. We're building an AI-native engineering platform supporting the modernization of mission-critical healthcare systems serving millions of Veterans nationwide. The platform is designed for deployment across federal enterprise environments and is being engineered to align with FedRAMP security controls, Zero Trust principles, and federal compliance requirements. The product has executive sponsorship, committed users, and a customer investing in long-term modernization. Our engineering team is intentionally small, giving every engineer meaningful ownership and direct influence over product direction. We don't simply build AI-powered software, we build software with AI. This is not another chatbot. Using LLMs, AI agents, secure identity architectures, and AI-assisted development is simply how we engineer. What You’ll Do: Design AI Identity Architecture Design identity services supporting autonomous and multi-agent AI systems. Establish secure identities for AI agents, enterprise services, users, and external integrations. Define identity lifecycles for AI agents, including provisioning, credential management, rotation, and decommissioning. Build reusable identity capabilities that scale across the AI platform. Authentication & Authorization Design and implement modern authentication and authorization frameworks for AI agents and platform services. Implement OAuth 2.0, OpenID Connect (OIDC), JWT, service principals, mutual TLS (mTLS), and delegated authorization models. Apply least-privilege and Zero Trust principles throughout AI workflows. Build fine-grained authorization models controlling AI access to enterprise data, APIs, tools, and services. Enterprise Identity Integration Integrate AI platforms with enterprise identity providers such as Microsoft Entra ID, Okta, Active Directory, and other IAM solutions. Enable secure identity federation across cloud and on-premises environments. Design secure service-to-service authentication supporting distributed AI architectures. Collaborate with enterprise security teams to align AI identity with organizational security standards. Secure Agent & Tool Access Design secure frameworks governing how AI agents discover, authenticate to, and invoke enterprise APIs, databases, and external tools. Build authorization models controlling agent capabilities and delegated permissions. Protect sensitive enterprise resources through policy-driven access controls. Implement secure credential handling and secrets management across AI workflows. Platform Engineering Develop reusable identity services, SDKs, APIs, and libraries supporting secure AI application development. Automate identity provisioning, credential lifecycle management, and authorization policies. Improve developer productivity through standardized identity services and secure engineering patterns. Partner with platform engineers to integrate identity services into the AI platform architecture. Governance & Auditability Ensure every AI action is authenticated, authorized, attributable, and auditable. Implement identity-aware logging, traceability, and policy enforcement. Support compliance and governance requirements for highly regulated environments. Partner closely with AI Security Engineers to establish secure-by-design AI development practices. What We’re Looking For: Bachelor's degree in Computer Science, Software Engineering, Cybersecurity, Information Systems, or a related technical discipline (or equivalent professional experience). 7+ years of software engineering, platform engineering, identity engineering, or cloud security experience. Experience designing authentication and authorization architectures for enterprise applications. Strong knowledge of OAuth 2.0, OpenID Connect (OIDC), JWT, SAML, PKI, and modern identity protocols. Experience integrating enterprise identity providers such as Microsoft Entra ID, Okta, Active Directory, or similar IAM platforms. Experience building secure REST APIs, microservices, and distributed systems. Knowledge of Zero Trust Architecture, RBAC, ABAC, delegated authorization, and identity federation. Experience with cloud platforms (Azure, AWS, or Google Cloud). Strong programming skills in Python plus experience with Go, Java, or TypeScript. Excellent communication, analytical, and problem-solving skills. Experience designing secure systems that enable innovation rather than restrict it. Expertise in identity and access management. Hands-on experience with cloud-native architecture and modern authentication frameworks. Strong ability to stay current with emerging AI technologies and evolving identity standards. Ability to collaborate effectively across software engineering, security, and AI disciplines. Willing and able to take ownership of difficult technical challenges and build elegant, innovative solutions. Nice to Have: Experience developing AI platforms, Agentic AI systems, or Large Language Model (LLM) applications. Experience securing Retrieval-Augmented Generation (RAG) systems and AI tool integrations. Familiarity with Model Context Protocol (MCP) and secure AI tool invocation. Experience with HashiCorp Vault, Azure Key Vault, AWS Secrets Manager, or similar secrets management platforms. Experience implementing identity services in Kubernetes and cloud-native environments. Experience with AI governance, Responsible AI, or AI platform security. Familiarity with LangGraph, LangChain, CrewAI, Semantic Kernel, AutoGen, or similar AI orchestration frameworks. Experience supporting Federal Government or healthcare environments. Identity or cloud certifications such as Microsoft Identity and Access Administrator, CISSP, Security+, CCSP, or cloud security certifications are a plus. What’s In It for You? The Opportunity to support high-visibility federal missions A culture that values innovation, growth, and collaboration Access to cutting-edge tools and technologies Comprehensive benefits for you and your family A career path that rewards ambition and performance If you’re ready to push boundaries, sharpen your skills, and join a team that is passionate about building what’s next, we’d love to meet you. Apply today and let’s build a future together! LTS shares salary ranges to promote transparency. Compensation ranges are provided for informational purposes, and final compensation may vary based on experience, skills, location, and role requirements. LTS is committed to offering eligible employees comprehensive benefits that will provide them with options intended to meet their needs and the needs of their family.