Lead AI/ML Engineer – GenAI, LLM, RAG

Job Title: Lead AI/ML Engineer – GenAI, LLM, RAG Location: Eden Prairie, MN (Remote) Employment Type: Contract (W2 through ZipStaff — No C2C or 1099) About the OpportunityZipStaff is seeking a Lead AI/ML Engineer to design, build, and deploy enterprise Generative AI solutions at a major healthcare organization.You will sit with a cross-functional team (one product manager, a senior lead, three developers, plus data scientists, data engineers, and application developers) and own production LLM work plus Responsible AI controls. This is a hands-on lead seat — not a research-only role and not a prompt-only role. What You’ll Do: • Architect and develop production Generative AI and LLM solutions. • Design and implement RAG, vector search, and knowledge-retrieval platforms. • Build scalable APIs, AI services, and cloud-native ML / LLM infrastructure. • Establish evaluation for quality, accuracy, groundedness, and safety. • Lead Responsible AI: bias mitigation, hallucination reduction, security, privacy, and compliance controls. • Partner with product, business, and engineering on high-value use cases. • Evaluate emerging AI technology and recommend what to adopt. • Influence and mentor engineers on the delivery team.

: • 10+ years in software engineering, machine learning, or AI engineering. • 5+ years building and deploying LLM or Generative AI solutions in production. • Bachelor’s in Computer Science, Engineering, Data Science, or a related field. • Strong Python and modern software-engineering practices. • Cloud platforms (Azure or AWS). • Hands-on RAG, vector databases, prompt engineering, and AI application development. • Proven lead of complex technical initiatives across functions. • Responsible AI, governance, privacy, and security in a regulated environment. • Ability to work on-site in Eden Prairie, MN. • Must be legally authorized to work in the United States without sponsorship now or in the future.

: • Healthcare or another regulated industry. • Production evaluation frameworks (groundedness, safety, accuracy). • Mentoring and platform-building, not only feature delivery.