Note: The job is a remote job and is open to candidates in USA. UnitedHealth Group is a global organization that delivers technology-enabled care and health services to help people live healthier lives. The Senior Manager of AI/ML Engineering will lead the engineering team responsible for the intelligence layer of digital solutions, overseeing enterprise AI strategy, architecture, deployment, evaluation, governance, and operational delivery. The role also focuses on developing engineering talent and ensuring AI capabilities are safe, measurable, performant, and scalable.
Responsibilities
- Lead, manage, and empower a high-performing engineering team responsible for designing, building, and deploying the intelligence layer for digital consumer applications
- Direct the architectural strategy and technical execution for LLM workflows, prompt chains, agentic behaviors, RAG patterns, copilots, and classification/summarization systems aligned to business goals and risk profiles
- Establish engineering standards, prompt strategies, tool-calling patterns, and safety guardrails to ensure AI solutions are explainable, testable, and governable across the enterprise
- Drive team delivery and continuous improvement using enterprise-approved AI tools to streamline workflows, automate complex technical tasks, and optimize engineering velocity
- Oversee the implementation of evaluation datasets, scoring rubrics, model-performance testing, and failure-mode analysis to continuously improve output quality, accuracy, latency, and cost efficiency
- Evaluate emerging AI/ML trends, industry advancements, and novel architectures to inform solution design, technology roadmaps, and strategic innovation
- Partner with Data Engineering leadership to ensure AI applications integrate with trusted, governed, and enterprise-grade data pipelines
- Collaborate with cross-functional executive leadership, QA, Responsible AI, security, privacy, compliance, and architecture teams to ensure AI components fulfill enterprise compliance and risk standards
- Champion production readiness, model observability, drift monitoring, and thorough technical documentation to enable steady-state supportability
- Mentor, coach, and develop engineering talent, setting clear performance goals, conducting reviews, and cultivating an inclusive culture of engineering excellence
Skills
- Bachelor's degree in Computer Science, Data Science, AI, or a related technical field, OR 4+ years of equivalent software/AI engineering experience in lieu of a degree
- 8+ years of experience in software engineering, data science, machine learning, or AI engineering
- 4+ years of practical engineering experience building and deploying production AI applications (including LLMs, RAG patterns, vector search, embeddings, prompt engineering, and agent frameworks)
- 4+ years of strong hands-on Python engineering experience, including model APIs, orchestration frameworks, data pipelines, and evaluation tooling
- 3+ years of technical leadership or engineering management experience leading and developing engineering teams
- 3+ years of experience designing testable, governable AI workflows and applying Responsible AI practices (mitigating hallucination risks, bias/fairness concerns, and model safety risks)
- Proven experience leading engineering teams in building and scaling LLM-enabled applications and copilots within enterprise settings
- Demonstrated experience establishing controlled testing, evaluation frameworks, scoring rubrics, and model monitoring prior to broad rollout
- Experience developing AI/ML solutions within healthcare, consumer digital platforms, or large-scale consumer applications
- Proven professional background as an ML Engineer, AI Engineer, Applied Scientist, Data Scientist with engineering depth, or Forward-Deployed Engineer with AI specialization
- Proven solid cross-functional collaboration skills with Responsible AI, security, legal, compliance, and enterprise architecture teams
Benefits
- A comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401k contribution
- Flexibility to work remotely from anywhere within the U.S.
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