Sr AI/ML Engineer - Hybrid in MN or DC - Remote elsewhere

Role

As a Senior AI/ML Engineer, you will design and build advanced machine learning and generative AI solutions for enterprise healthcare applications. Work includes developing LLM applications, RAG pipelines, and agentic AI systems while ensuring production-grade reliability, performance, safety, and governance.

Key Responsibilities

• Design and deploy generative AI and NLP solutions (search, summarization, extraction, conversational AI, decision support).
• Develop and fine-tune LLM applications using commercial and open-source models.
• Design and implement retrieval-augmented generation (RAG) pipelines: document ingestion, chunking, embedding generation, and vector database integration.
• Build agentic AI systems (single- and multi-agent) with tool use, reasoning, planning, and autonomous task execution.
• Implement evaluation and monitoring frameworks including hallucination detection, bias monitoring, and human-in-the-loop evaluation.
• Develop safety and governance controls: prompt hardening, policy enforcement, and responsible AI guardrails.
• Productionize AI/ML pipelines with CI/CD, testing, monitoring, and observability in cloud-native environments.
• Collaborate with product, platform, and data science teams to translate requirements into scalable AI solutions.

Requirements

• 5+ years in machine learning, AI engineering, or applied data science, including production ML systems.
• 5+ years developing Python-based ML systems using frameworks such as PyTorch, TensorFlow, or Hugging Face.
• 3+ years building Generative AI or LLM applications (prompt engineering, model fine-tuning, LLM API integrations).
• 2+ years designing RAG systems and vector search pipelines.
• 1+ year building agentic AI systems (tool-calling, planning frameworks, multi-agent workflows).
• 1+ year using AI-assisted development or “vibe coding” tools such as Codex, Claude Code, Cursor, or Windsurf.

Preferred Qualifications

• Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
• Experience optimizing LLM latency, cost, and performance in production.
• Experience deploying AI systems on cloud platforms (AWS, Azure, GCP).
• Experience working in regulated environments with responsible AI governance requirements.

Location & Work Model

• Remote work permitted anywhere in the U.S.; hires in Minneapolis or Washington, D.C. must work in-office a minimum of four days per week.
• Remote employees must adhere to UnitedHealth Group’s Telecommuter Policy.

Compensation & Benefits

• Salary range: $91,700 to $163,700 annually (full-time).
• Benefits include a comprehensive benefits package, incentive and recognition programs, equity stock purchase, and 401(k) contribution.

Notes

• Role focuses on production-grade, enterprise AI for healthcare with emphasis on safety, monitoring, and responsible AI practices.