AI/ML Engineer

Description:
The AI/ML Engineer will be responsible for researching, designing, implementing, and managing advanced AI/ML solutions with a focus on agentic architectures. This role involves close collaboration with developers, UX designers, business analysts, and system stakeholders to deliver intelligent, production-grade solutions.
The ideal candidate has strong experience with large language models (LLMs), context engineering, and multi-agent systems, along with a deep understanding of AI governance, security, and performance optimization.
Responsibilities:

• Design, develop, and deploy AI-powered agentic solutions and autonomous workflows
• Build and implement Retrieval-Augmented Generation (RAG) systems using vector databases
• Develop and manage scalable AI/ML models and applications using Python and modern AI frameworks
• Integrate large language models (LLMs) via APIs (OpenAI, Hugging Face, Azure AI, etc.)
• Implement context engineering strategies to improve model performance and relevance
• Collaborate with cross-functional teams including developers, analysts, and UX designers
• Ensure AI solutions meet governance, security, and compliance requirements
• Develop and enforce AI guardrails, content filtering, and safety mechanisms
• Implement Model Context Protocol (MCP) for secure data access across systems
• Optimize model performance, token usage, and overall cost efficiency
• Conduct testing, evaluation, and continuous improvement of AI systems
• Support deployment, monitoring, and lifecycle management of AI solutions

Required Skills:

• 4+ years of experience in AI/ML engineering or advanced data science
• Proven experience building and deploying production-grade autonomous agents
• Strong expertise in context engineering
• Hands-on experience with frameworks such as LangChain, LangGraph, CrewAI, or AutoGPT
• Experience implementing RAG architectures with 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 Model Context Protocol (MCP)
• Experience with AI guardrails, content filtering, and safety controls
• Strong understanding of data privacy and handling sensitive data (PII/PHI)

Preferred Skills:

• 2+ years of experience building multi-agent or autonomous workflows
• Experience optimizing LLM cost, token usage, and performance
• Familiarity with enterprise AI deployment patterns and scalability
• Experience working in regulated environments (healthcare/government)

Eligibility:

• Must be eligible to work in the U.S. without sponsorship.
• Must be able to work onsite in Austin, TX (3 days/week required)

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