Senior AI / Machine Learning Engineer (LLM & Autonomous Systems)
Role summary
We are seeking an experienced AI/Machine Learning Engineer to design, develop, and deploy production-grade AI systems, focusing on LLM-powered applications, autonomous agents, and RAG-based solutions for enterprise decision-making and process automation. Responsibilities include building RAG pipelines, integrating LLMs via APIs, implementing AI governance and safety controls, optimizing LLM performance and cost, and ensuring secure data handling. The role requires 4+ years in AI/ML engineering or data science with experience in LLM systems, RAG, Python, and AI frameworks.
Overview
We are seeking an experienced
AI / Machine Learning Engineer
to design, develop, and deploy intelligent, production-grade AI systems. This role focuses on building
LLM-powered applications, autonomous agents, and RAG-based solutions
to support enterprise decision-making and process automation.
Key Responsibilities
- Design, develop, and deploy
AI-driven applications and autonomous agent systems
- Build and optimize
Retrieval-Augmented Generation (RAG)
pipelines using vector databases
- Integrate
LLMs via APIs
and implement scalable AI workflows
- Collaborate with developers, analysts, and UX teams to deliver end-to-end solutions
- Implement
AI governance, safety controls, and model evaluation frameworks
- Optimize
LLM performance, cost, and token efficiency
- Ensure secure handling of
sensitive data (PII/PHI)
- Contribute to architecture decisions for scalable, enterprise-grade AI systems
Required Skills
- 4+ years in
AI/ML engineering or advanced data science
- 4+ years building
production-grade AI/LLM systems
- Strong experience with:
- LangChain / LangGraph / CrewAI / AutoGPT
- RAG architectures + vector databases
- Python + AI/ML frameworks (OpenAI, Hugging Face, Azure AI)
- Experience integrating
LLMs into enterprise systems
- Knowledge of
AI governance, guardrails, and model lifecycle management
- Understanding of
data privacy and secure AI design
Preferred Skills
- Experience with
multi-agent systems / autonomous workflows
- LLM
cost optimization and scaling strategies
- Familiarity with
enterprise AI deployment patterns
Location & Duration
- Hybrid (Austin, TX – Local candidates only)
- Duration: ~4 months (extension possible)