We are looking for Senior AI Engineer for our client in Irvine, CA.
Job Title: Senior AI Engineer
Job Location: Irvine, CA
Job Type: Contract
Job Overview:
Pay Range: $56hr - $61hr
Requirement/Must Have:
- 1+ years of 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).
- Strong programming skills (Python preferred).
- Experience with Databricks and Apache Spark.
- Solid understanding of data pipelines, distributed systems, and API design.
Responsibilities:
- Build and operationalize LLM-powered applications using Retrieval-Augmented Generation (RAG), embeddings pipelines, and prompt orchestration frameworks.
- Design and implement vector search systems using Amazon OpenSearch.
- Develop graph-based knowledge systems using Amazon Neptune for relationships, lineage, and explainability.
- Integrate supporting infrastructure such as Amazon ElastiCache (Redis) for session state and caching, and DynamoDB for scalable, low-latency data access.
- Implement agentic workflows using frameworks such as LangGraph, AutoGen, CrewAI (or equivalent).
- Integrate with LLM frameworks like LangChain, LlamaIndex for tool calling, retrieval orchestration, and context management.
- Define standards for tool integration and context-sharing patterns.
- Evaluate LLM models and retrieval strategies across latency, cost, accuracy, and context limitations.
- Design and build scalable data pipelines using Databricks and Apache Spark.
- Implement data ingestion and transformation pipelines, document processing, and embedding generation.
- Ensure high data quality standards including validation, completeness, consistency, and monitoring.
- Implement data governance frameworks including data classification, access controls, retention policies, and auditability.
- Develop backend services exposing AI capabilities through secure and scalable APIs.
- Define best practices for API contracts, reliability, and enable reusability of platform capabilities.
- Build and manage CI/CD pipelines for AI and data workloads.
- Deploy production systems using Docker and Kubernetes.
- Implement deployment strategies including blue/green deployments, canary releases, rollback strategies, and feature flags.
- Ensure system reliability through monitoring, alerting, observability, and secrets management.
- Define and track GenAI quality metrics including grounding, retrieval relevance, response consistency, latency, and cost per request.
- Implement prompt/version tracking and continuous improvement workflows.
- Implement secure AI systems with access control, data protection policies, and responsible AI guardrails.
- Ensure compliance with best practices in AI safety, data privacy, monitoring, and auditability.
Nice to Have:
- 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 and agent-based architectures.
Skills:
- Strong problem-solving and analytical thinking.
- Ability to communicate complex AI concepts clearly.
- Collaborative and cross-functional mindset.
- Ownership-driven and proactive execution.
Qualification And Education:
- Bachelor s or Master s degree in Computer Science, Data Science, AI, or a related field.
- Proven experience building production-grade AI platforms and systems.
- Strong background in end-to-end AI/ML lifecycle delivery.