ML Infrastructure Architect

Job Details Title: AI /ML Lead Location: Minneapolis, MN Duration: Long term Contract Summary : We are looking for a Senior AI/ML Lead /Architect to lead the design and delivery of enterprise-grade AI solutions with a strong focus on Generative AI in healthcare. This role requires deep expertise in RAG systems, Agentic AI, MLOps, and AI governance, along with hands-on experience building production-ready AI platforms. Key Responsibilities:

• AI Project Delivery Lead end-to-end execution of AI/ML & GenAI projects
• Translate business requirements into scalable AI architectures
• Work closely with stakeholders and engineering teams for successful delivery

GenAI & Solution Architecture

• Design and implement RAG-based systems and LLM applications
• Build HIPAA-compliant AI solutions for healthcare use cases
• Develop systems for: Claims processing automation Medical document / metadata extraction Intelligent recommendation systems

AI Governance & Compliance

• Drive AI governance and Responsible AI practices
• Support AI review processes and ensure compliance (HIPAA, data privacy)
• Implement ethical and secure AI frameworks

Team Leadership

• Lead and mentor AI/ML Engineers & Data Scientists
• Conduct architecture reviews, code reviews, and technical discussions

MLOps & Engineering

• Build and manage ML/LLM pipelines and CI/CD workflows
• Implement model monitoring, drift detection, and observability
• Ensure best practices in versioning, deployment, and scalability

Do you have experience in Prompt engineering?, * Core AI/ML & GenAI Strong experience in Generative AI (LLMs, RAG, Agentic AI)

• Hands-on with Vector Databases (Pinecone, FAISS, Milvus, Weaviate)
• Experience building production-grade AI systems
• LLM Engineering Experience with: Embeddings & retrieval systems Prompt engineering frameworks (LangChain, PromptFlow) Multi-agent systems (CrewAI / LangGraph)
• MLOps / LLMOps CI/CD pipelines (GitHub Actions or similar) Monitoring tools (MLflow, LangSmith, Prometheus, Grafana) Model lifecycle management & drift detection
• Technical Stack Python TensorFlow / PyTorch / scikit-learn Cloud: AWS / Azure / Google Cloud Platform
• Healthcare Experience (Must Have) Experience working with: Claims processing / clinical data / EHR HIPAA compliance, PHI handling, data security, * Architect-level professional with end-to-end AI system ownership
• Hands-on experience building real-world GenAI solutions
• Strong in both architecture + execution