Sr Product Manager, AI and Product Office - Boston, MA or Remote

UnitedHealth Group•Boston, MA

1d•$159,300 - $273,200•Remote

About The Position

The Sr Product Manager, AI & Product Office owns AI-enabled products that help the Chief AI & Product Officer (CAIPO) drive Optum Health's enterprise AI-enabled product strategy, Agenix solutions portfolio, and product capability agenda. Serving as strategist, builder, and owner of the outcome, this role defines the problem with the people who do the work, decides what gets built and why, and takes each product from first prototype through deployment and measurement. This individual is accountable for measurable enterprise value: whether what shipped changed care for patients and care teams, whether it did so appropriately, and whether it earns the return required to scale. The Sr Product Manager keeps the work focused on the smallest version that can prove or disprove a bet, and brings clinical, operational, technology, and governance partners into one team rather than a chain of handoffs. This is a job for a builder. The team is just starting, and you will help build it and shape how it innovates, at the highest level. The office is small today, and that is by design: its leverage is the enterprise AI investment it drives across Optum Health. You will write, prototype, and analyze with AI tools every day, and you will be where care is delivered, not only in meetings about it. The AI & Product Office is building a small, cross-functional product team: product management, engineering, product design, service design, deployment, and clinical, working alongside care team members from each local market team. The team embeds with a local Optum Health market team to find problems with the people who do the work, then design, build, deploy, and measure the products that fix them. What the team learns in the first market is written down as the method for the next one. 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.

Requirements

7+ years of product management experience shipping software products used by operational, clinical, or frontline users
Experience in the healthcare industry and/or within a large, complex, matrixed organization
Experience to has shipped an AI, machine learning, or large language model feature to production and measured what it changed
Experience to has shipped products with engineering teams both inside and beyond their own team
Experience in using AI tools in your own work today and has built with them: an agent, automation, or large language model tool you designed, built, and ran, at work or as a personal project We will ask you about it in the interview
Works as a senior individual contributor: owns hard problems end to end, working across functions to deliver them
Working proficiency in the tools this office builds with: GitHub and AI coding and agent tools, alongside the analytics and presentation tools executives use
Demonstrated business acumen: builds a business case, defines metrics, writes SQL or equivalent, and reads a rollout result without an analyst in the room
Demonstrated ability to work at the enterprise level and at a single market's level, and to tell which one a given decision belongs to
Proven exceptional communication skills, including with executive-level audiences; solid writing: decisions, findings, and disagreements in this office are written down, so the writing is the work
Proven ability to build cross-functional relationships at all levels of the organization and lead toward shared goals without formal authority

Nice To Haves

Bachelor's degree in Business, Technology, Product Management, Healthcare, Data/Analytics, or a related field; MBA, MHA, or other advanced degree welcome
Experience with care delivery, care coordination, patient access, or scheduling products
Experience with electronic health record integration (Epic, athenahealth, eClinicalWorks) and healthcare data standards such as FHIR and HL7
Experience taking an AI capability through an enterprise governance or review process in healthcare
Experience building a zero-to-one product inside a large organization, or at an early-stage company
Familiarity with value-based care and how care patterns affect cost and quality

Responsibilities

Embed with local market teams in primary care, specialty, home and community, and virtual settings to understand how care is delivered, and turn what you observe into written problem statements ranked by the people who do the work
Define, before build begins, the smallest version of a product that can prove or disprove the bet, the outcome measure that will decide it, and the business case it must meet to scale
Partner with care team members as design partners from the first conversation, not as reviewers at the end
Determine which problems belong to a single market and which belong to the enterprise, and shape each product accordingly
Own the roadmap and backlog for your products, making tradeoffs across scope, speed, risk, and cost, and write each decision down with its reasoning and what would change it
Run the work as one team rather than a chain of handoffs, with cycle time measured in weeks
Work with the team's engineers and with great Optum Health engineering teams: set direction, write the specifications and evaluations the build is held to, and review what ships
Build prototypes, analyses, and internal tools yourself with AI coding and agent tools, and continuously improve them
Partner with finance, technology, data, security, legal, privacy, compliance, care teams, and other stakeholders to deliver products that are responsible, secure, and enterprise-ready, including through Optum Health's AI review and governance process
Define, with clinical and governance partners, what an AI feature must get right, how it is measured, the bar it must clear before it reaches users, and the bar it must clear before it takes on more autonomy
Establish baselines before launch for operational, clinical, and financial outcomes, such as access, time to care, and cost, so the change can be attributed
Measure whether each patient got the right care, not only whether a proxy metric moved
Report what changed since the last period, including results that show something did not work, and turn results into decisions to stop, change, or scale
Build the value case for scaling each product, and partner with finance to validate it
Develop change management and adoption plans with the deployment manager, so the people affected understand the purpose, impact, readiness requirements, and expected value of each product
Write down what the team learns each week so it is reviewed on cadence and turned into decisions
Hand proven products to scaled delivery teams, and write the playbook so the next team can stand up the same product from what is written down, without you
Raise the AI fluency of the market teams you work with, helping the people closest to the work use and build with AI safely