To Apply for this Job Click Here
AI Engineer — GenAI & Data Platform (AWS) (Hybrid, 4 days onsite)(4 open roles)
Location: Irvine, CA & Los Angeles, CA
Length: 5 month contract (potential extension)
Overview:
We are seeking two AI Engineers to design, build, and scale a production-grade Generative AI and Data Platform on AWS. This 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 and partner closely with product and engineering teams to operationalize AI capabilities in externally facing applications, driving evolution toward agentic AI systems.
Responsibilities:
GenAI Enablement
Build and operationalize LLM-powered applications using RAG, embeddings pipelines, and prompt orchestration. Design vector search systems and graph-based knowledge systems for relationships, lineage, and explainability. Implement agentic workflows and define standards for tool integration and context-sharing patterns.
Data Pipelines and Knowledge Engineering
Design scalable data pipelines using Databricks and Spark, including document processing, chunking, and embedding generation. Ensure data quality, governance, and lineage tracking.
Backend Services and APIs
Develop secure, scalable backend services exposing AI capabilities through well-defined API contracts with reliability best practices.
Deployment and MLOps
Build CI/CD pipelines and deploy production systems using Docker and Kubernetes with blue/green and canary deployment strategies. Ensure observability, monitoring, and cost optimization.
LLM Quality and Observability
Track GenAI quality metrics including grounding, retrieval relevance, and latency. Implement prompt tracking and continuous evaluation workflows.
Security and Compliance
Implement access control, data protection, and responsible AI guardrails in alignment with AI safety and privacy standards.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field
- Proven experience building production-grade AI platforms and systems
- Strong background in end-to-end AI/ML lifecycle delivery
- Strong problem-solving skills with the ability to communicate complex AI concepts clearly
- Collaborative, ownership-driven, and proactive in execution