AI Agent Engineer - HHSC

AI Agent Engineer (LLM/RAG Specialist)
• Title/Level: Software Developer 2
• Category: Applications / Software Development
• Positions: 3
• Location Austin Texas (Hybrid)
• Mode of Interview- Video

I. DESCRIPTION OF SERVICES
The client requires the services of three (3) Software Developer 2 professionals to support application development initiatives under the IT Staff Augmentation Contract (ITSAC).
The selected Candidates will be responsible for designing, developing, and implementing modern software solutions with a strong focus on AI-driven agentic systems and intelligent automation.
Key Responsibilities
• Research, design, develop, and maintain software applications
• Build and deploy AI-powered autonomous agents and workflows
• Develop and implement Retrieval-Augmented Generation (RAG) architectures
• Integrate Large Language Models (LLMs) via APIs and enterprise systems
• Collaborate with developers, UX designers, business analysts, and stakeholders
• Ensure compliance with AI governance, security, and data privacy standards
• Implement AI guardrails, safety controls, and content filtering mechanisms
• Optimize system performance, scalability, and cost efficiency
• Participate in testing, debugging, and production deployment
AI Agent Engineering Focus
• Design and develop agentic AI solutions and autonomous workflows
• Implement context-aware systems using Model Context Protocol (MCP)
• Build scalable AI solutions supporting enterprise decision-making

II. MINIMUM QUALIFICATIONS
Candidates must meet or exceed the following requirements:
Years Type Required Skills / Experience
4 Required Experience in AI/ML engineering or advanced data science
4 Required Building and deploying production-grade autonomous agents
4 Required Strong experience in context engineering
4 Required Experience with LangChain, LangGraph, CrewAI, or AutoGPT
4 Required Implementation of RAG architectures using vector databases
4 Required Proficiency in Python and AI/ML tools (OpenAI, Hugging Face, Azure AI)
4 Required Integration of LLMs via APIs and AI lifecycle management
4 Required Experience with Model Context Protocol (MCP) and secure data access
4 Required Implementation of AI safety, guardrails, and content filtering
4 Required Knowledge of data privacy and handling PII/PHI
Preferred Qualifications
Years Type Preferred Skills
2 Preferred Multi-agent or autonomous workflow development
2 Preferred LLM optimization (cost, tokens, performance)
2 Preferred Enterprise AI deployment and scalability