Job description

Title: 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. About the Role 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 LangGraph and LangChain. Design single-agent and multi-agent architectures based on business and technical requirements. Build RAG and retrieval workflows using vector search, embeddings, and PostgreSQL/pgVector. 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 WebSockets 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. Required Technical Skills Strong experience with Generative AI / LLM applications Hands-on experience with Agentic AI LangGraph and/or LangChain Python & AWS RAG / Retrieval-Augmented Generation Vector databases / Vector Search / Embeddings PostgreSQL SQL / Text-to-SQL Experience with LLM tool calling / function calling Understanding of multi-agent architectures and orchestration Strong understanding of prompt engineering and system prompts Experience addressing LLM hallucination, grounding, context management, and response accuracy Strong software engineering and system design experience

Requirements

Must-haves

Title: Principal AI Engineer – Agentic AI
Location: Irvine, CA (Hybrid)
Employment Type: Contract to Hire
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.
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 LangGraph and LangChain.
Design single-agent and multi-agent architectures based on business and technical requirements.
Build RAG and retrieval workflows using vector search, embeddings, and PostgreSQL/pgVector.
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 WebSockets 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.
Required Technical Skills
Strong experience with Generative AI / LLM applications

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aimachine learningmlllmsqlawspython

Platform: catsone
Effort: medium