AI Agent Engineer
Austin, TX – Hybrid – Only Locals
5 months Contract
INPERSON INTERVIEWS
Position will be 3 days remote with 2 days (Tues & Wed) required to be onsite at the location listed above. Program will only allow candidates who are LOCAL TO THE AUSTIN AREA ONLY (Within 50-mile radius). **Subject to change per the hiring team**
Please do not submit candidates who are currently out of state and are planning to move to Texas. Candidates must already reside in Texas.
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.
II. CANDIDATE SKILLS AND QUALIFICATIONS
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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.
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Years
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Required/Preferred
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Experience
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4
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Required
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experience in AI/ML engineering or advanced data science
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4
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Required
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Proven track record of building and deploying production-grade autonomous agents.
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4
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Required
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Strong experience in context engineering
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4
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Required
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Deep experience with LangChain, LangGraph, CrewAI, or AutoGPT.
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4
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Required
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Experience implementing RAG architectures using vector databases
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4
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Required
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Proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI)
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4
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Required
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Experience integrating LLMs via APIs Knowledge of AI governance, model lifecycle management, and evaluation
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4
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Required
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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
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4
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Required
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Understanding of data privacy and handling of sensitive data (PII/PHI)
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2
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Preferred
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Experience building multi-agent or autonomous agentic workflows
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2
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Preferred
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Experience optimizing LLM cost, token usage, and performance
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2
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Preferred
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Familiarity with enterprise AI deployment patterns and scalability considerations
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