Title: AI Agent Engineer
Duration: 5 Months (3 Yrs Ext)
Location: Austin, TX 78751. The working position is Hybrid - On Site and Telework.
Position is ONSITE/Hybrid at the location listed above (with some hybrid work determined by the hiring manager). The program will only accept LOCAL ONLY candidates for this position.
The program will only allow candidates who are LOCAL TO THE AUSTIN AREA ONLY.
Level Description
4-7 years of experience in the field or in a related area. Familiar with standard concepts, practices, and procedures within a particular field. Relies on limited experience and judgment to plan and accomplish goals. A certain degree of creativity and latitude is required. Works under limited supervision with considerable latitude for the use of initiative and independent judgment.
Job Description
Researching, designing, implementing and managing software programs. Testing and evaluating new programs. Working closely with other developers, UX designers, business and systems analysts.
Additional job details and special 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
Required Skills:
4 years of Required Experience in AI/ML engineering or advanced data science
4 years of Required Proven track record of building and deploying production-grade autonomous agents.
4 years of Required Strong experience in context engineering
4 years of Required Deep experience with LangChain, LangGraph, CrewAI, or AutoGPT.
4 years of Required Experience implementing RAG architectures using vector databases
4 years of Required Proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI)
4 years of Required Experience integrating LLMs via APIs Knowledge of AI governance, model lifecycle management, and evaluation
4 years of 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 years of Required Understanding of data privacy and handling of sensitive data (PII/PHI)
Preferred Skills:
2 years of Preferred Experience building multi-agent or autonomous agentic workflows
2 years of Preferred Experience optimizing LLM cost, token usage, and performance
2 years of Preferred Familiarity with enterprise AI deployment patterns and scalability considerations
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