Lead AI​/ML Engineer - Full Stack Development - Remote

Overview

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities.

Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

The Lead AI/ML Engineer is a strategic and hands on technical leader responsible for designing, building, and deploying advanced AI and machine learning solutions across the full application stack. This role blends deep expertise in AI/ML, cloud native architectures, and full stack software engineering with cross functional leadership, driving innovation, operational excellence, and scalable AI adoption across the organization.

You ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

• Model Development & Deployment
  • Architect, develop, and deploy scalable AI/ML platforms and full stack application solutions, spanning model training, inference, APIs, and user experiences
  • Implement AI/ML computing infrastructures and application stacks using frameworks such as AWS Bedrock core/Google ADK, with orchestration using AWS Agent Core for multi agent workflows
  • Design end to end pipelines covering data ingestion, feature processing, model serving, and observability
• Full Stack Engineering
  • Build and maintain production grade backend services and APIs using Java and Python
  • Develop and integrate frontend and lightweight UI components (e.g., dashboards, internal tools) to operationalize AI workflows and analytics
  • Apply modern software engineering practices including CI/CD pipelines, containerization, and cloud native deployment
• Cross functional Collaboration
  • Partner closely with data scientists, product managers, UX teams, and business stakeholders to translate complex business requirements into scalable AI and full stack solutions
  • Act as a bridge between research, engineering, and product teams to ensure solutions are practical, performant, and maintainable
• AI Strategy & Governance
  • Define and document architecture roadmaps, reference architectures, and standard operating procedures for AI/ML systems
  • Ensure alignment with enterprise standards for reliability, security, fairness, transparency, and regulatory compliance
• Technical Leadership & Mentorship
  • Lead technical design reviews, guide architectural decisions, and oversee model evaluation, optimization, and deployment cycles
  • Mentor junior and senior engineers, setting clear expectations for code quality, system design, and operational readiness
• Innovation & Research
  • Conduct applied research to advance capabilities in Generative AI, NLP, NLU, computer vision, and predictive modeling
  • Stay current with emerging tools, architectures, and industry trends, and translate them into actionable engineering practices
• Operational Excellence
  • Lead disaster recovery and business continuity planning for AI and application infrastructure
  • Monitor, tune, and continuously improve deployed models and services for performance, accuracy, scalability, and cost efficiency
• Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows and decision-making.

• AI/ML solutions are production ready, scalable, and fully integrated into full stack applications
• Teams are aligned on clear architectures, standards, and best practices
• Engineers are mentored effectively, and delivery velocity improves without sacrificing quality or reliability
• AI systems demonstrate measurable business impact, operational stability, and trustworthiness

• Bachelor s or…