Strategic Product Manager, GenAI

College Board

1d•$80,000 - $157,000•Remote

About The Position

As the Strategic Product Manager, GenAI, you define the right problems to solve and connect strategy to execution. In this pivotal role, you will act as the bridge between the Studio’s high-level strategy and its on-the-ground execution. You’ll own a portfolio of internal GenAI products and experiments from discovery through implementation, focused on two outcomes: (1) driving high-value, scalable use cases with measurable organizational impact, and (2) enabling scaled adoption and integration by working cross-functionally with Talent, Technology, and Strategy partners in service of our mission. You will also own a critical portfolio of AI engagement strategy, ensuring use cases align to College Board’s horizontal “everyone benefits” approach. You translate user pain points and business outcomes into a clear plan, including where we build, buy, or partner (e.g., with model providers), and how we measure value. You will partner closely with the Technical Product Manager, who leads complex technical builds, while you focus on defining what should be built and why. Throughout this work, you ensure initiatives connect directly to meaningful "Moments that Matter" for our staff. You are a systems thinker who defines problems, validates solutions, and drives behavioral change, anchoring decisions in evidence drawn from both qualitative insight and quantitative metrics.

Requirements

5+ years of experience as a Product Manager or Product Owner, leading and owning digital product implementations in AI and/or automation-centered solutions, driving strategy, roadmaps, and a prioritized backlog from discovery through delivery.
Proven ability to lead cross-functional teams, partnering with engineering/ML, design, and research; writing crisp requirements and negotiating technical/product tradeoffs.
Proven strength in problem framing, user research, and evidence-based decision-making, with the ability to translate insights into clear product and strategy choices.
Strong stakeholder engagement and change management abilities, including communicating scope, milestones, releases, and risks, and driving adoption and behavior change across teams.
Experience leading enterprise-wide transformations and/or internal tool adoptions, with a clear understanding that shipping is only half the work and adopting is the other half.
Ability to advocate on behalf of users, including experience pushing for new ways of working while maintaining trust-based relationships across divisions and senior leaders.
Ability to evaluate emerging GenAI technologies with clear metrics that track quality, safety, latency, and cost, while translating findings into pragmatic pilots and actionable guidance for non-technical teams and L&D.
User-centered practices, including running interviews, conducting usability tests, and translating insights into prioritized stories with clear acceptance criteria and measurable outcomes.
Commitment to responsible AI by design, embedding privacy, security, accessibility, and compliance into all product decisions and documenting mitigations and guardrails.
Operational excellence in practice, including establishing team mechanisms (rituals, templates, checklists) and coordinating vendors and tools to deliver outcomes on time and with quality.
The ability to travel 4-5 times a year to College Board offices or on behalf of College Board business.
A passion for expanding educational and career opportunities and mission-driven work
Authorization to work in the United States for any employer
Curiosity and enthusiasm for emerging technologies, with a willingness to experiment with and adopt new AI-driven solutions and a comfort learning and applying new digital tools independently and proactively.
Clear and concise communication skills, written and verbal
A learner's mindset and a commitment to growth: welcoming diverse perspectives, giving and receiving timely, respectful feedback, and continuously improving through iterative learning and user input.
A drive for impact and excellence: solving complex problems, making data-informed decisions, prioritizing what matters most, and continuously improving through learning, user input, and external benchmarking.
A collaborative and empathetic approach: working across differences, fostering trust, and contributing to a culture of shared success.

Responsibilities

Drive high-value, future-proof GenAI experimentation (70%)
Translate business problems into technically feasible GenAI solutions with clear hypotheses and success metrics.
Manage end-to-end launches, moving from discovery to prototype to pilot to scale with responsible-by-design practices, including security, privacy, and accessibility.
Ensure delivery against scope and milestones by identifying risks, removing blockers, coordinating vendors/licenses, and aligning cross-functional teams.
Define hypotheses, success metrics, and evaluation methods for GenAI pilots; instrument experiments to measure productivity, quality, safety, and ROI.
Scan emerging practices and technologies and translate them into pragmatic pilots that fit College Board contexts.
Use qualitative and quantitative data to assess performance, inform tradeoffs, and guide next steps.
Define the adoption path: who pilots, what training or literacy is needed, and how we scale.
Join strategic conversations and co-own internal GenAI engagement (30%)
Participate in relevant strategic scoping for enterprise-wide workforce strategy and AI enablement
Lead deep discovery and user research (interviews, surveys, workflow analysis) to identify high-friction points in the employee lifecycle (e.g., mid-year reviews, finance workflows, onboarding, etc.) where AI can deliver outsized value.
Rigorously define user problems before solutions are engineered, distinguishing between needs that require technical builds (e.g., AI Agents) and those that require process changes or literacy interventions.
Design and execute non-technical experiments (e.g., light prototypes, process pilots) to validate business value and user trust before committing technical resources.
Act as the primary strategist for the "AI Champions" network, evolving it from a passive audience into an active engine for peer-to-peer training, feedback collection, and decentralized adoption.
Define trust requirements for our tools by partnering with AI Governance to translate complex ethical considerations (e.g., hallucination risks) into clear, user-friendly features and guidelines that build user confidence.
Document repeatable models so divisions can adopt solutions with confidence and consistency.