Senior AI Engineer

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.