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.