Product Manager, AI Solutions

BGBx

1d•$200,000 - $250,000•Remote

About The Position

BGBx is hiring a Product Manager, AI Solutions to guide the development of AI-powered solutions for life science companies. The role defines product direction, priorities, and tradeoffs; turns client needs into requirements; and tests those requirements with clients before work enters the roadmap. It works closely with engineers, data scientists, client solutions teams, and clients in discovery, demonstrations, and validation. A central focus is productization: transforming solutions built for individual clients into configurable products that can serve future clients. The position is part of the AI technology team and reports to the SVP, AI Capabilities and Products. The successful candidate should understand AI and data products well enough to assess feasibility, challenge estimates, and write buildable requirements, but does not need to be an engineer. The role also establishes product development practices, supports client scoping, creates lightweight prototypes and demos, explains models and methods in accessible language, and works within data, privacy, and AI governance standards.

Requirements

At least 8 years of product management experience, including at least one product or feature taken from discovery through launch.
Experience writing requirements, setting priorities, and managing a roadmap with input from engineering and business stakeholders.
Working knowledge of AI and data product development, including APIs, data pipelines, and large language model applications, sufficient to judge feasibility and challenge estimates.
Comfort leading client discovery conversations and presenting to senior stakeholders in plain language.
Familiarity with AI-assisted prototyping tools and willingness to use them to build lightweight demos.
Clear written communication skills.
Bachelor's degree required.

Nice To Haves

Experience in pharmaceuticals, life sciences, medical communications, or another regulated industry, especially commercial, medical, or market access work.
Familiarity with healthcare data such as claims, prescription, or healthcare professional data, and the associated privacy and compliance requirements.
Exposure to forecasting, scenario planning, or analytics products.
Experience in a consulting or agency environment where work is scoped and billed to clients.
Experience with a modular product in which client needs map to different parts of a broad menu.
Experience with software, data, or AI products.

Responsibilities

Establish product development practices, including PRD standards, sign-off before development, acceptance before release, and coaching business owners on requirements; apply these practices to in-house and partner builds.
Own the roadmap for AI solutions and recommend priorities and tradeoffs through the AI governance process, explaining decisions to leadership, engineering, and client teams.
Write requirements and acceptance criteria with business owners and validate them with clients, engineers, and data scientists before work begins and before release.
Lead client discovery conversations to identify underlying business questions and determine whether BGBx solutions fit.
Track client requests across pitches and engagements, identify recurring needs, and advocate for reusable product capabilities.
Support scoping and estimates for client engagements by assessing feasibility with client and technical teams based on current product capabilities.
Lead productization by turning client-specific solutions into configurable products, defining configuration requirements with client teams and engineers, and validating results with clients.
Decide whether client needs should be addressed through custom builds or added to the product roadmap.
Build lightweight prototypes and tailored demonstrations using AI-assisted tools.
Explain models and methods in plain language and involve data science and behavioral science experts when their methods differentiate the product.
Follow data, privacy, and AI governance standards and document decisions so engineering teams can support, extend, or retire released products.