Logic Software Solutions

Compensation

Full Description

Job Description: Senior Gen AI Cloud Engineer (Gen AI Vertex AI Focus) Location: USA (Hybrid - San Francisco Santa Clara)Experience:& 10+ YearsStart Date:& Immediately About the Role We are seeking a highly seasoned and hands-on& Senior GCP AI Cloud Engineer& to join our dynamic team. You will be at the forefront of designing, building, and scaling cutting-edge Generative AI solutions on the& Google Cloud Platform (GCP). This role requires deep expertise in the GCP AI/ML stack, especially& Vertex AI& and the& Gemini& model family, and a proven ability to translate complex product requirements into robust, production-grade systems. You will be a key player in driving our AI strategy and implementation on GCP. Key Responsibilities • GCP AI Solution Architecture Development: • Design, build, and deploy sophisticated Generative AI applications on GCP, with a strong focus on& AI agents& and multi-step reasoning systems built within the& Vertex AI& ecosystem. • Leverage and fine-tune foundational models, including the& Gemini& family (e.g., Gemini Pro, Gemini Ultra), using& Vertex AI& for model training, deployment, and management. • Implement and orchestrate complex LLM workflows using& Vertex AI Agent Builder& and frameworks like& LangChain& on GCP for tasks such as Retrieval-Augmented Generation (RAG), summarization, and agentic behaviors. • Architect and implement& RAG pipelines& on GCP, integrating& Vertex AI Search& and& Conversational AI& or custom solutions with vector databases. • GCP Infrastructure Data Engineering: • Architect and implement end-to-end AI solutions leveraging a wide array of GCP services. • Integrate GCP services for& storage& (Cloud Storage, BigQuery),& serverless logic& (Cloud Functions, Cloud Run),& data processing& (Dataflow, Dataproc), and& messaging& (Pub/Sub) to create comprehensive, scalable AI pipelines. • Build and maintain reliable and cost-effective data pipelines on GCP to support AI model training and inference. • Rapid Prototyping Model Evaluation on Vertex AI: • Use& Vertex AI Model Garden& and& Vertex AI Evaluation& to quickly conduct experiments, benchmark new LLM models, and analyze their performance, features, and cost. • Implement MLOps practices using& Vertex AI Pipelines,& ML Metadata, and& Model Monitoring& to ensure model reliability and performance in production. • Engineering Excellence Security on GCP: • Employ& Infrastructure as Code (IaC)& using& Terraform& to provision and manage GCP resources in a repeatable and scalable manner. • Implement robust security measures for AI systems using GCP’s& Identity and Access Management (IAM),& Cloud KMS& for encryption, and ensure compliance with data governance policies using& Data Loss Prevention (DLP)& and& VPC Service Controls. • Champion software engineering best practices, including version control (Git), CI/CD using& Cloud Build, and MLOps principles. • Collaboration Leadership: • Work closely with Gen AI Leads and cross-functional team members to refine the product backlog, provide technical estimates, and deliver on sprint commitments. • Mentor junior engineers and evangelize best practices in Gen AI development on GCP. Mandatory Technical Skills Experience (Primary) • GCP AI/ML Gen AI Stack: • Vertex AI Platform:& Deep, hands-on experience with the core services of& Vertex AI, including Model Training, Batch and Online Prediction, Feature Store, Pipelines, and Model Registry. • Gemini Foundational Models:& Production-level experience integrating with the& Google Gemini& model family (especially Pro 1.x) via API endpoints and within the Vertex AI environment. • LLM Frameworks Agents:& Thorough, implementation-level exposure to building& LLM agents& using& LangChain& and/or& Vertex AI Agent Builder. A deep understanding of agentic patterns and tools. • Vector Databases:& Practical experience with vector databases like& Vertex AI Vector Search& (preferred), Pinecone, or Chroma for building semantic search systems. • GCP Development Services: • GCP Core Services:& Extensive hands-on experience with core GCP infrastructure and serverless services:& Cloud Storage, Cloud Functions, Cloud Run, IAM, BigQuery, and Pub/Sub. • Programming:& Excellent programming skills and high proficiency in& Python& (primary) for Gen AI orchestration and scripting. Secondary proficiency in& PySpark& or& Java& is highly desirable. • AI-Assisted Development:& A thorough understanding and practical use of AI-assisted development tools like& Cursor& for rapid prototyping and code generation. Secondary Desirable Skills • Infrastructure as Code:& Proficiency in& Terraform& for managing and automating GCP infrastructure. • Multi-Cloud (AWS):& Experience with AWS AI/ML services (e.g., SageMaker, Bedrock) is a plus. • Security Compliance:& Strong understanding of GCP security principles, specifically& IAM, Cloud KMS, and VPC Service Controls& for securing AI models and data. • MLOps:& Familiarity with MLOps tools and practices on GCP for model versioning, monitoring, and lifecycle management. Personal Attributes • Self-Starter:& Ability to work autonomously in a remote setting, manage priorities, and take ownership of projects from conception to delivery. • Innovative Problem Solver:& Passion for exploring new technologies and a knack for solving complex, ambiguous problems. • Analytical Mindset:& Strong ability to analyze data, model outputs, and system performance to make informed decisions. • Excellent Communicator:& Clear and concise communication skills, capable of collaborating effectively with both technical and non-technical stakeholders. • Agile:& Comfortable working in a fast-paced, agile environment. What We Offer • A remote-first work culture. • Opportunity to work on cutting-edge GCP AI technologies and complex challenges. • A collaborative and intellectually stimulating environment. • Competitive compensation and benefits.