[Hiring] Lead AI/ML Engineer @UnitedHealth Group

Role Description

This is a high-impact technical leadership role within the Optum Tech AI Transformation team, supporting key enterprise initiatives such as the Real-Time AI Underwriting platform. You will own the technical direction and people leadership for a squad of AI/ML engineers, driving strategic engineering efforts. Beyond building, you will lead, mentor, govern, and ensure that everything your team delivers meets the highest standards of quality, compliance, and Responsible AI. You'll serve as a bridge between engineering execution and leadership vision, ensuring AI investments translate into measurable, production-grade business outcomes.

You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges.

• Design, develop, and deploy production-grade AI-powered solutions—spanning classical ML, Generative AI (LLMs, RAG, Graph RAG), and multi-agent orchestration frameworks—to address complex business challenges with emphasis on responsible and secure AI practices.
• Own the end-to-end AI/ML technical roadmap, defining architectural direction, choosing optimal technologies, and establishing engineering and coding standards for the team's portfolio.
• Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement across the development lifecycle, optimizing team productivity and operational efficiency.
• Evaluate emerging trends and technologies (such as Agentic AI, foundation models, fine-tuning, and enterprise AI tooling) to inform high-quality solution design and strategic innovation.
• Drive MLOps maturity across development pipelines, overseeing model versioning, CI/CD for ML, retraining automation, drift detection, and production monitoring.
• Ensure compliance and ethical governance by aligning solutions with enterprise policies, Responsible AI principles, and data privacy regulations (HIPAA/PHI handling).
• Lead, mentor, and develop a team of 5–10 direct/indirect AI/ML engineers, setting clear goals, conducting regular 1:1s, and fostering a high-performance, self-managed culture.
• Own and conduct robust technical reviews (architecture, design, and code reviews) to enforce rigorous standards, security posture, and pythonic best practices.

Qualifications

• 10+ years of software development experience with a strong engineering and architecture foundation.
• 2+ years of hands-on experience in AI/ML project implementation (full lifecycle from ideation, data analysis, model development through production deployment).
• Hands-on experience with NLP (text processing, embeddings, transformers, NER, text classification, or conversational AI).
• Working experience with GenAI (RAG pipelines, prompt engineering, LLM integration, fine-tuning techniques like LoRA, and enterprise deployment).
• Experience or strong working knowledge of Agentic AI development (agentic workflows, tool orchestration, multi-agent systems, or planning frameworks).
• Solid Python programming skills with deep proficiency in production-grade coding, code reviews, and enforcing standards.
• Driver’s License and access to a reliable transportation.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field (or equivalent professional experience).
• Experience with MLOps tooling (MLflow, Weights & Biases, Kubeflow, etc.) for experiment tracking, model registry, and automation.
• Familiarity with Responsible AI frameworks (bias detection, fairness metrics, model explainability like SHAP/LIME, and adversarial red-teaming).
• Knowledge of Graph RAG, knowledge graphs, and ontology-based reasoning systems.

Benefits

• Comprehensive benefits package.
• Incentive and recognition programs.
• Equity stock purchase.
• 401k contribution (all benefits are subject to eligibility requirements).

Application Deadline

This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.