Senior Director, AI CoE Product Lead (Secondment - 12 Months)

Pfizer•New York City, NY

1d•Hybrid

About The Position

The AI CoE Product Lead is responsible for driving product as a horizontal function across the Ai CoE verticals while having tight collaboration with the broader Platform and Product teams within Digital. This function will be embedded in the Strategic Operations, Global Support & Enablement organization, providing focused leadership and product expertise that span all the most critical strategic initiatives within the AI Coe.

Requirements

Must have a bachelor's degree with at least 12+ years of experience.
15+ years of product management or product development experience
Significant experience in a high-growth environment, taking products from inception to launch and building an effective product team.
Experience with agile/lean and cloud-native development, big data and analytics.
Experience scaling products, overseeing their build from MVP to mass scale.
Experience in managing a cross-functional team in the healthcare industry.
A demonstrated business acumen and history of accountability and performance delivery, leading teams to meet or exceed objectives.
Strong analytical skills with an emphasis on data-driven decision making.
Familiarity with common project management tools for sprint planning, roadmaps, and analytics, etc.
Entrepreneurial spirit.
Ability to operate and quickly respond to emerging needs.
Strong product mindset: Ability to quickly research, design, build and launch digital products to meet company and market needs.
Excellent written and verbal communication skills as well as the ability to influence key partners and stakeholders.
Permanent work authorization in the United States.

Nice To Haves

Master's degree with at least 10+ years of experience; OR a PhD with 7+ years of experience; OR a MD with 5+ years of experience.
Additional consideration will be given to individuals who, in addition to the above, have regulated medical device or digital healthcare industry, or related experience.
Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.

Responsibilities

Own the end-to-end colleague experience that spans Loom, MemX, and Forge49 with the Ai Marketplace tools, the product no single engineering pillar owns, defining how a colleague’s work moves across platforms as one coherent journey.
Overseeing engineering pillars’ roadmaps.
Adoption evidence sets what Platform Engineering teams build next.
Maintain product-minded ownership of the three-platform experience, validated through continuous engagement with colleagues across R&D, Commercial, PGS, and enabling functions.
Own the adoption model for the three platforms, including role-cohort rollout on a regular cadence, so capability reaches the colleagues who carry the heaviest load first.
Operate a central enablement hub that owns the rollout method, AI literacy, and practitioner training, focused on how colleagues think and work with these tools, not only how to click through them.
Orchestrate a federated champions network.
Own the feedback path from the field back into the roadmap, ensuring adoption friction is surfaced as a prioritization signal rather than absorbed silently.
Own colleague journey mapping and friction analysis across the three platforms, the qualitative discipline that makes “voice of the divisions” a practice rather than a slogan.
Investigate why colleagues route around the governed path, and translate those findings into product and roadmap direction for the engineering pillars.
Serve as the qualitative complement to adoption measurement: measurement shows what is happening, design research explains why.
Collaborate with the Platform teams to drive adoption, and adoption measurement for the three platforms as the source of truth, governed-path versus shadow-path usage, reuse rate, leakage, and hours recovered.
Own value realization for Loom, MemX, and Forge49 (including AI Marketplace tools).
Feed the three-platform adoption and value metrics into the AI value scorecard as its source for those platforms, so there is one instrumentation pipe and one owner rather than competing dashboards.