Technical Product Manager

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 (security, privacy, 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 and inform next steps.

Participate in relevant technical scoping for enterprise-wide releases.

Ship with quality and responsibility by aligning to security, privacy, accessibility, and compliance standards, and by documenting decisions and guardrails.

Report progress and impact through transparent metrics, dashboards, and release communications.

Communicate roadmap, releases, and outcomes clearly to stakeholders; drive change management that builds trust and adoption.

Design and run experiments (e.g., A/B tests and internal pilots) and use the results to decide whether to roll out widely, adjust the approach, or sunset the product

Document repeatable models so divisions can adopt with confidence.

5+ years leading and owning digital product implementations in AI 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.

Strong stakeholder engagement and change management abilities, including communicating scope, milestones, releases, and risks, and driving adoption and behavior change across teams.

Hands-on technical fluency, partnering with engineering on core building blocks such as APIs, data workflows, system integrations, prompt design and versioning, retrieval and data prep, function/tool use, monitoring and analytics; able to guide discussions on architecture, security, and testing without being an engineer yourself.

Track record of evidence-based experimentation and iteration, including running pilots, A/B tests, and data-driven evaluations to decide when to scale, pivot, or sunset solutions.

Experience shipping LLM/AI or automation features in production workflows, such as assistants, retrieval/RAG, agents, summarization or classification tools.

Ability to evaluate emerging GenAI technologies with clear metrics (e.g., gold sets, offline/online tests, human-in-the-loop review) and 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 on time with quality.

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.

Application review will begin immediately and will continue until the position is filled.

This role is expected to accept applications for a minimum of 5 business days.

While the may vary, it generally includes: resume and application submission, recruiter phone/video screen, hiring manager interview, performance exercise such as live coding, a panel interview, a conversation with leadership and reference checks.

The hiring range for this role is $80,000 – $157,000.

Your exact salary will depend on your location, experience, and how your background compares to others in similar roles at the College Board.

We aim to make our best offer upfront—rooted in fairness, transparency, and market data.

We adjust salaries by location to ensure fairness, no matter where you live.