Lead AI/ML Engineer - Remote Nationwide or Hybrid in MN/DC

About the position As a Lead AI/ML Engineer within Optum Rx, you will lead the design, development, and scaling of advanced machine learning systems and artificial intelligence solutions that directly impact pharmacy benefits, patient care, and clinical workflows. You will serve as the technical lead for complex AI/ML initiatives, designing conversational virtual assistants and driving modern engineering practices across cross-functional teams. This role collaborates with enterprise architecture, capability teams, and vendors to architect robust, secure, and scalable solutions for our core conversational chatbot platform utilized by both internal and external stakeholders.\nYou’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. Responsibilities Lead the design, development, and production deployment of AI/ML solutions, translating models and algorithms into scalable, secure, and reliable software used in enterprise systemsServe as a technical lead for complex AI/ML initiatives, owning end-to-end implementation from design through deployment and operational supportUse enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement across teamsApply advanced knowledge of machine learning, deep learning, statistics, and experimental methodologies to build high-quality, data-driven solutionsPartner closely with product, business, and engineering stakeholders to identify high value use cases and deliver AI solutions that solve real OptumRx business problemsLead AI solution architecture and design in collaboration with the Enterprise Architecture team, core capability teams, and major platform vendors (including Microsoft, Palantir, and MongoDB) to identify optimal designs for our core conversational chatbot platformMaintain comprehensive solution architecture and network architecture diagrams for our core conversational chatbot platform utilized by multiple internal and external stakeholdersDrive modern engineering practices across teams, including automation-first development, code reuse, observability, and CI/CD adoption for AI systemsChampion AI/MLOps best practices, ensuring models and pipelines are production-ready, monitored, and continuously improvedInfluence architectural decisions by applying broad domain and technology expertise to balance performance, scalability, security, and maintainabilityEnforce and promote enterprise security, privacy, and quality standards within AI/ML solutions, proactively identifying and mitigating riskMentor and guide engineers across teams, acting as a subject-matter expert and escalation point for AI/ML engineering challengesCommunicate complex AI/ML concepts and results clearly to technical and non-technical audiences, including senior leadershipEvaluate emerging trends to inform solution design, optimize architecture, and drive strategic enterprise innovationRequirements Bachelor’s degree or equivalent experience; 4+ years of software engineering experience may substitute for a degree5+ years of professional software engineering experience using Python, Java, Scala, or similar programming languages3+ years of experience designing, training, and deploying machine learning or deep learning models into production systems2+ years of experience building and managing MLOps frameworks, continuous integration/continuous deployment (CI/CD) pipelines, and containerized deployments (e.g., Docker, Kubernetes)2+ years of experience writing SQL and working with relational or non-relational database systems (such as MongoDB)Nice-to-haves Master’s or PhD degree in Computer Science, Artificial Intelligence, Data Science, or a related technical fieldExperience architecting, designing, and maintaining solution/network architecture diagrams for conversational chatbot solutions, virtual assistants, or natural language processing (NLP) applicationsExperience collaborating with enterprise architecture teams and leading technical design discussions with cloud and platform vendors (e.g., Microsoft, Palantir, MongoDB).Experience with Large Language Models (LLMs), prompt engineering, fine-tuning, and retrieval-augmented generation (RAG)Proven solid understanding of data privacy, model governance, and ethical AI practices within the healthcare sectorExcellent communication and collaborative problem-solving skills, with a proven ability to lead technical initiatives and mentor team membersBenefits comprehensive benefits packageincentive and recognition programsequity stock purchase401k contribution