Apply to Software Developer 1688

Austin, TX
Software Developer - Solicitation# 529601688
Texas Health and Human Services Commission (HHSC)

Researching, designing, implementing and managing software programs. Testing and evaluating new programs. Working closely with other developers, UX designers, business and systems analysts.
AI Agent Engineer Designs and develops AI-driven agentic solutions, including autonomous workflows and Retrieval-Augmented Generation (RAG) systems, to enhance productivity, automate processes, and support intelligent decision-making with a focus on governance, security, and cost efficiency.
Position will be 3 days remote with 2 days (Tues & Wed) required to be onsite. Program will only allow candidates who are LOCAL TO THE AUSTIN AREA ONLY (Within 50-mile radius). **Subject to change per the hiring team**
 

Minimum Requirements: Candidates that do not meet or exceed the minimum stated requirements (skills/experience) will be displayed to customers but may not be chosen for this opportunity.
Actual Years Experience	Years Experience Needed	Required/ Preferred	Skills/Experience
	4	Required	experience in AI/ML engineering or advanced data science
	4	Required	Proven track record of building and deploying production-grade autonomous agents.
	4	Required	Strong experience in context engineering
	4	Required	Deep experience with LangChain, LangGraph, CrewAI, or AutoGPT.
	4	Required	Experience implementing RAG architectures using vector databases
	4	Required	Proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI)
	4	Required	Experience integrating LLMs via APIs Knowledge of AI governance, model lifecycle management, and evaluation
	4	Required	Experience implementing and extending the Model Context Protocol (MCP) to provide LLMs with secure, standardized access to local and remote data sources Experience implementing AI guardrails, content filtering, and safety controls
	4	Required	Understanding of data privacy and handling of sensitive data (PII/PHI)
	2	Preferred	Experience building multi-agent or autonomous agentic workflows
	2	Preferred	Experience optimizing LLM cost, token usage, and performance
	2	Preferred	Familiarity with enterprise AI deployment patterns and scalability considerations

I need Three References

 

Reference Name (Required):
Title (Optional)
Company Name (Required):
Phone Number (Required include area code):
E-mail address (Optional):
Professional Relationship (Optional):

  Peer                                                                      Co-Worker                                                                                                                                                Supervisor

  Customer                                                             End-User                                                                                                                                                   Subordinate

 

Reference Name (Required):
Title (Optional)
Company Name (Required):
Phone Number (Required include area code):
E-mail address (Optional):
Professional Relationship (Optional):

  Peer                                                                      Co-Worker                                                                                                                                                Supervisor

  Customer                                                             End- User                                                                                                                                                 Subordinate

 

Reference Name (Required):
Title (Optional)
Company Name (Required):
Phone Number (Required include area code):
E-mail address (Optional):
Professional Relationship (Optional):

  Peer                                                                      Co-Worker                                                                                                                                                Supervisor

  Customer                                                             End- User                                                                                                                                                 Subordinate