Job Description

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries.

     

JOB DESCRIPTION:

Working at Abbott

At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You’ll also have access to:

• Career development with an international company where you can grow the career you dream of.
• Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year.
• An excellent retirement savings plan with a high employer contribution
• Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree.
• A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune.
• A company that is recognized as one of the best big companies to work for as well as the best place to work for diversity, working mothers, female executives, and scientists.

The Opportunity

As a Staff Product Manager - Enterprise AI Platform, you will be responsible for product ownership of the Enterprise AI Platform itself: the enterprise AI control plane and the paved road that enables teams across Abbott to build, deploy, and operate AI/ML and agentic systems safely and quickly. This role works closely with enterprise and division teams that consume the platform, including AI Product Managers, AI/Agentic Engineering teams, Applied Data Scientists, and division engineering and science teams, to translate their needs into a prioritized platform capability roadmap that drives adoption, scalability, governance, and operational excellence across the enterprise.

What You'll Do

• Own the product roadmap for the AI Platform — the control plane and paved-road services (registry, orchestration, evaluation, observability, cost governance, guardrails) in partnership with the Platform Engineering Lead and Architect.

• Gather and prioritize platform requirements from every consuming team across the enterprise, balancing competing requests against roadmap capacity.

• Define and evolve the paved road — the self-service tooling, templates, and standards that let teams build, deploy, and operate AI/ML and agentic systems without reinventing governance, security, or observability each time.

• Act as the platform's product owner: maintain the backlog, write and prioritize platform requirements, and represent the voice of consuming teams in engineering planning.

• Define and track adoption, satisfaction, and time-to-onboard metrics across consumer teams and use them to steer the roadmap.

• Partner with the Platform Engineering Lead and Platform/Solutions Architect to sequence platform investment against the Platform Roadmap published by Strategy & Portfolio.

Education and Experience You’ll Bring

Required Qualifications

• 8–10+ years of product management experience, including managing platform, infrastructure, or developer-facing products.

• Real, hands-on experience as a product manager for a platform or infrastructure product consumed by other engineering teams (an internal developer platform, API platform, data platform, or MLOps platform).

• Experience as a product manager for an AI/ML platform specifically (feature stores, model registries, agent-orchestration frameworks, evaluation/observability tooling).

• Strong technical depth to credibly represent concepts such as model/agent registries, Model/MCP Gateway, orchestration, evaluation frameworks, and control-plane governance in engineering planning.

• Bachelor's degree in a related field or equivalent professional experience.

• Strong stakeholder-management skills across multiple internal consuming teams with competing priorities.

Preferred Qualifications

• Experience as a product manager for an AI/ML platform specifically (feature stores, model registries, agent-orchestration frameworks, evaluation/observability tooling).

• Experience building or scaling a “paved road” / internal developer platform practice.

• Experience in a highly regulated enterprise where platform governance, auditability, and control-plane requirements are a first-order design constraint, not an afterthought.

Misc: This is an onsite role at Abbott location in IL. This is not a remote role/opportunity.

Apply Now

• Learn more about our health and wellness benefits, which provide the security to help you and your family live full lives: www.abbottbenefits.com
• Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity.
• Connect with us at www.abbott.com, on Facebook at www.facebook.com/Abbott, and on Twitter @AbbottNews.

     

The base pay for this position is

$129,300.00 – $258,700.00

In specific locations, the pay range may vary from the range posted.

JOB FAMILY:

IT Services & Solutions Delivery

     

DIVISION:

BTS Business Technology Services

        

LOCATION:

United States > Abbott Park : AP06C

     

ADDITIONAL LOCATIONS:

United States > Chicago : Willis Tower Building 233 S Wacker Dr.

     

WORK SHIFT:

Standard

     

TRAVEL:

Yes, 10 % of the Time

     

MEDICAL SURVEILLANCE:

Not Applicable

     

SIGNIFICANT WORK ACTIVITIES:

Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day), Keyboard use (greater or equal to 50% of the workday)

     

Abbott is an Equal Opportunity Employer of Minorities/Women/Individuals with Disabilities/Protected Veterans.

EEO is the Law link - English: http://webstorage.abbott.com/common/External/EEO_English.pdf

EEO is the Law link - Espanol: http://webstorage.abbott.com/common/External/EEO_Spanish.pdf