Title: Principal AI Engineer – Agentic AI | Contract to Hire | Irvine, CA (Hybrid) | AS

Central Business Solutions•Irvine, CA

7d•Hybrid

About The Position

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.

Requirements

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.
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

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.