AI Agent Engineer - AI/ML Engineer – Agentic Systems
Role summary
Cogent Data Solutions LLC is seeking an AI Agent Engineer/AI/ML Engineer specializing in Agentic Systems for a hybrid role in Austin, TX, with a state client, Texas Health and Human Services Commission. The role requires a minimum of 4 years of experience in AI/ML engineering or advanced data science, with a proven track record in building and deploying production-grade autonomous agents. Key technical skills include deep experience with frameworks like LangChain, LangGraph, CrewAI, or AutoGPT, implementing RAG architectures, proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI), and integrating LLMs via APIs. The engineer will also focus on context engineering, AI governance, data privacy (PII/PHI), AI guardrails, and optimizing LLM cost and performance.
Hello,
Cogent Data Solutions LLC trying to reach you regarding a job opportunity. The role is
AI Agent Engineer - AI/ML Engineer – Agentic Systems (
Software Developer ) for one of our direct clients. Please take a look at the job description below and please send your updated resume.
**Role
*:***
AI Agent Engineer - AI/ML Engineer – Agentic Systems (
Software Developer )
***Location
:*
Hybrid (onsite -
*Tues & Wed )*
- Austin, TX**
*Client Name:*
Texas Health and Human Services Commission
.
( State client )
*Job Qualifications/ Skills:*
Minimum 4 years experience
AI/ML Engineer – Agentic Systems or Autonomous AI Engineer)
LangChain / LangGraph / CrewAI / AutoGPT
- experience in AI/ML engineering or advanced data science
- Proven track record of building and deploying production-grade autonomous agents.
- Strong experience in context engineering
- Deep experience with LangChain, LangGraph, CrewAI, or AutoGPT.
- Experience implementing RAG architectures using vector databases
- Proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI)
- Experience integrating LLMs via APIs Knowledge of AI governance, model lifecycle management, and evaluation
- 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
- Understanding of data privacy and handling of sensitive data (PII/PHI)
- Experience building multi-agent or autonomous agentic workflows
- Experience optimizing LLM cost, token usage, and performance
- Familiarity with enterprise AI deployment patterns and scalability considerations
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.