Title: Principal AI Engineer – Agentic AI | Contract to Hire | Irvine, CA (Hybrid) | AS
Listed on 2026-08-19
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Principal AI Engineer – Agentic AI
Location:
Irvine, CA (Hybrid)
Employment Type:
Contract to Hire Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. 12+ years of software engineering experience. 5+ years building AI/ML applications.
We are seeking a Senior/Principal AI Engineer to design and build production-grade Agentic AI and Generative AI applications that enable Client's executives to interact with operational data through a conversational interface. The ideal candidate will have strong experience building LLM-powered applications, AI agents, RAG solutions, tool-calling workflows, and data-grounded AI systems, with a strong focus on accuracy, trust, scalability, and production readiness.
Key Responsibilities- Design and develop Agentic AI / LLM-based applications for enterprise use cases.
- Build conversational AI experiences that allow users to query complex operational data using natural language.
- Develop agent workflows using frameworks such as Lang Graph and Lang Chain.
- Design single-agent and multi-agent architectures based on business and technical requirements.
- Build RAG and retrieval workflows using vector search, embeddings, and PostgreSQL/pg Vector.
- Develop controlled tool-calling and SQL-based data retrieval workflows.
- Implement mechanisms to prevent hallucinations and ensure responses are grounded in authoritative data.
- Design validation processes for data availability, freshness, accuracy, and provenance before generating responses.
- Integrate AI agents with enterprise data sources and APIs.
- Work with AWS-based data and AI infrastructure.
- Evaluate and optimize LLM application performance, including latency, token usage, cost, and response quality.
- Design approaches for managing long conversational context, intent routing, and context isolation.
- Implement real-time status/progress updates for long-running AI workflows using technologies such as Web Sockets or Server-Sent Events.
- Establish evaluation frameworks and metrics for AI accuracy, grounding, hallucination, and overall system quality.
- Collaborate with product managers, data engineers, architects, and business stakeholders.
- Lead technical discussions, architecture decisions, code reviews, and mentor other engineers.
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