Senior AI Engineer (GenAI + Data Platform – AWS)- CA(Onsite)

• Job Description: Senior AI Engineer (GenAI + Data Platform – AWS) • Location: CA, Irvine(Onsite) Role Summary We are seeking a Senior AI Engineer to design, build, and scale a production-grade Generative AI and Data Platform on AWS. The role focuses on enabling LLM-powered capabilities through vector search, graph-based knowledge systems, and governed data pipelines. The ideal candidate will own end-to-end delivery across the AI lifecycle, including: Data ingestion and knowledge curation Embeddings and retrieval systems Backend services and APIs CI/CD pipelines and deployment This role will closely partner with product and engineering teams to operationalize AI capabilities in externally facing applications and drive evolution toward agentic AI systems. Required Skills Strong experience in Generative AI / LLM systems (RAG, embeddings, prompt engineering) Hands-on experience with AWS ecosystem Expertise in: OpenSearch (vector search) Neptune (graph databases) DynamoDB and Redis (ElastiCache) Experience with: LangChain / LlamaIndex Agentic AI frameworks (LangGraph, AutoGen, CrewAI) Strong programming skills (Python preferred) Experience with Databricks and Apache Spark Solid understanding of: Data pipelines Distributed systems API design Preferred Skills Experience with: Model evaluation frameworks and LLM observability tools AI governance and compliance frameworks Kubernetes and advanced MLOps practices Familiarity with: Model Context Protocol (MCP) patterns Agent-based architectures Qualifications Bachelor’s or Master’s degree in: Computer Science / Data Science / AI / related field Proven experience building production-grade AI platforms and systems Strong background in end-to-end AI/ML lifecycle delivery Soft Skills Strong problem-solving and analytical thinking Ability to communicate complex AI concepts clearly Collaborative and cross-functional mindset Ownership-driven and proactive execution Mandatory Areas Must Have Skills • Skill 1 – Generative AI / LLM (RAG, embeddings, prompt engineering) • Skill 2 – AWS Cloud (OpenSearch, Neptune, DynamoDB, ElastiCache/Redis) • Skill 3 – Vector Search & Retrieval Systems (OpenSearch / vector DB) • Skill 4 – Graph Databases (Amazon Neptune, knowledge graphs) • Skill 5 – LLM Frameworks (LangChain / LlamaIndex) • Skill 6 – Agentic AI Frameworks (LangGraph / AutoGen / CrewAI) • Skill 7 – Databricks & Apache Spark (data pipelines, embedding pipelines) • Skill 8 – Backend/API Development (Python, scalable APIs, microservices) \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Domain Experience (If any) – • AI/ML Platform Engineering • Generative AI / LLM Applications • Data Platform / Big Data Engineering \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Must Have Certifications – • AWS Certification (Preferred): • AWS Certified Solutions Architect OR • AWS Certified Machine Learning Specialty OR • AWS Data Engineer Certification