Manager Data Analytics

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.

Primary Responsibilities:

Agentic AI Architecture & Delivery

Design and implement (multi) agentic workflows where LLMs plan, decompose tasks, invoke tools/APIs, and synthesize answers across heterogeneous data sources and services

Build retrieval augmented generation (RAG) and hybrid search pipelines to power robust questions answering over clinical and operational data

Design, code, test, document, and maintain high quality, scalable Big Data and cloud solutions

Develop scalable microservices and APIs for integrating agent capabilities into clinician tools and internal apps

Create prototypes/POCs and conduct design/code reviews to derisk delivery and raise engineering quality

LLMs, GenAI & Model Adaptation

Leverage and adapt LLMs; perform prompt engineering, grounding, guard railing, and domain adaptation for healthcare terminology and tasks

Establish evaluation frameworks (automatic + human in the loop) to measure faithfulness, helpfulness, bias, toxicity, privacy leakage, and overall quality

Data & Platform Engineering

Partner with data engineering to build feature/retrieval stores, embeddings pipelines, and ETL/ELT jobs on Spark/Databricks; design analytics models and rules engines

Define and develop APIs for integrations across the enterprise; improve data access patterns for low latency inference

Delivery, MLOps & Reliability

Own MLOps/LLMOps: CI/CD for models/prompts, automated tests (unit/contract/eval), versioning, lineage, rollback; enable blue/green or canary releases

Instrument SLOs/SLIs (latency, availability, hallucination/defect rate) and cost KPIs (tokens, GPU hours) with dashboards and alerts

Lead production deployments on internal platforms (e.g., UAIS) with strong observability, reliability, and cost controls

Security, Privacy & Compliance

Champion HIPAA and regulated industry controls; integrate access controls, PHI/PPI safeguards, data minimization, encryption, and auditability

Collaborate with legal, compliance, and clinical safety to operationalize Responsible AI principles

Product, Estimation & Collaboration

Analyze and define customer requirements; assist in defining product technical architecture and delivery roadmaps

Provide effort estimates and inputs for resource planning; collaborate with QA, architecture, and peer teams

Write technical documentation, support production, and mentor engineers, and keep skills current through continuous learning

Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

Bachelors in engineering, Computer Science, IT, or related fields

10+ years of experience in Data Engineering, Cloud Platform Engineering, and Enterprise Solution Architecture

5+ years of hands-on experience in Azure Databricks, Spark performance optimization, distributed computing, and designing scalable data platform architectures

3+ years of experience architecting and implementing Generative AI solutions leveraging LLMs, RAG frameworks, LangGraph, AI Agents, and enterprise AI platforms

Experience designing end-to-end cloud-native architectures on Azure, including data, analytics, AI, security, and governance frameworks

Experience leading architecture reviews, driving technical decision-making, and guiding engineering teams on scalability, reliability, security, and operational excellence

Solid expertise in defining enterprise data strategies, solution blueprints, architecture standards, and technology roadmaps

Demonstrated success in driving enterprise AI adoption, establishing best practices, and delivering AI-powered business solutions at scale

Demonstrated solid stakeholder management and communication skills, with the ability to influence leadership, align technology strategies with business objectives, and mentor senior engineering teams

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.