Job ID: JOB_ID_7685
About the Role
We are seeking an experienced AI Agent Engineer to join our team. This role involves researching, designing, implementing, and managing software programs with a focus on AI-driven agentic solutions. You will work closely with other developers, UX designers, business analysts, and systems analysts to enhance productivity, automate processes, and support intelligent decision-making. Our focus is on ensuring governance, security, and cost efficiency in all AI implementations.
Key Responsibilities
- Design and develop AI-driven agentic solutions, including autonomous workflows and Retrieval-Augmented Generation (RAG) systems.
- Enhance productivity, automate processes, and support intelligent decision-making.
- Ensure governance, security, and cost efficiency in AI implementations.
- Research, design, implement, and manage software programs.
- Test and evaluate new programs.
- Work closely with other developers, UX designers, business and systems analysts.
- Implement RAG architectures using vector databases.
- Integrate LLMs via APIs.
- Implement AI guardrails, content filtering, and safety controls.
- Understand data privacy and handling of sensitive data (PII/PHI).
- Optimize LLM cost, token usage, and performance.
- Contribute to enterprise AI deployment patterns and scalability considerations.
Minimum Requirements
- 4 years of experience in AI/ML engineering or advanced data science.
- 4 years of proven track record of building and deploying production-grade autonomous agents.
- 4 years of strong experience in context engineering.
- 4 years of deep experience with LangChain, LangGraph, CrewAI, or AutoGPT.
- 4 years of experience implementing RAG architectures using vector databases.
- 4 years of proficiency in Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI).
- 4 years of experience integrating LLMs via APIs.
- 4 years of knowledge of AI governance, model lifecycle management, and evaluation.
- 4 years of experience implementing and extending the Model Context Protocol (MCP) to provide LLMs with secure, standardized access to local and remote data sources.
- 4 years of experience implementing AI guardrails, content filtering, and safety controls.
- 4 years of understanding of data privacy and handling of sensitive data (PII/PHI).
- 2 years of experience building multi-agent or autonomous agentic workflows (Preferred).
- 2 years of experience optimizing LLM cost, token usage, and performance (Preferred).
- 2 years of familiarity with enterprise AI deployment patterns and scalability considerations (Preferred).
Additional Information
- This is a hybrid position requiring 3 days remote and 2 days onsite (Tuesdays & Wednesdays) in Austin, TX.
- Candidates must be LOCAL TO THE AUSTIN AREA ONLY (Within a 50-mile radius). No relocation will be provided.
- The start date is approximately 4/30/26.
- Public Sector experience is a must-have.
Special Requirements
Hybrid (3 days remote, 2 days onsite), Local to Austin area only (within 50-mile radius), Public Sector experience required.
Compensation & Location
Salary: $120,000 – $160,000 per year (Estimated)
Location: Austin, TX
Recruiter / Company – Contact Information
Email: ishek.kumar@steneral.com
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