Staff Technical Program Manager, Ads Measurement

Pinterest•San Francisco, CA

6h•Remote

About The Position

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. Pinterest Technical Program Managers deliver critical & strategic outcomes by directing and scaling engineering effort across organizational and functional boundaries. This role is within the Ads Measurement org, which is responsible for proving the value of Advertising at Pinterest. You will be driving development of new solutions, scaling of existing solutions, solving complex engineering problems, and driving ambiguous programs from inception to launch. Example programs: building new measurement products, optimizing delivery based on measurement source of truth, and driving new integrations.

Requirements

7+ years of experience as a technical program manager, or related experience.
Entrepreneurial spirit with strong leadership, who can develop and lead a new initiative from the ground up and thrive in ambiguity.
Passion for execution, and getting things done.
Solid technical background and ability to quickly understand technical designs, challenges and risks. Experience breaking down complex problems and driving decision making.
Strong analytical abilities, able to create & monitor metrics, proactively identify growth opportunities & incidents.
Strong written, verbal communication skills and comfort in communicating nuanced, and often technical, concepts to internal stakeholders or external partners.
Ability to influence teams & drive alignment among multiple stakeholders.
Demonstrated experience in creating and driving efficient processes at scale.
AI-first execution mindset: demonstrated ability to use GenAI to accelerate planning, program operations, and stakeholder communications—starting with AI drafts and applying strong judgment to validate, refine, and drive decisions.
Workflow design, AI fluency, data & insights orientation: experience turning repeatable program work into durable, low-toil mechanisms and improving decision-making by using GenAI (e.g., strong prompting, vibe coding lightweight scripts/tools, dashboards, data analysis and leveraging agents where appropriate).
Safety-by-design AI fluency: experience operating within AI governance expectations (risk assessment, data handling, model/output validation, auditability/traceability) and proactively identifying where AI use is not appropriate or requires additional controls.
Bachelor’s degree in a relevant field such as computer science, computer and information technology, or equivalent experience.

Nice To Haves

Prior experience working in ads space is preferred

Responsibilities

Own end-to-end program delivery for Ads Measurement initiatives: Drive planning → execution → launch for complex, cross-org measurement programs (e.g., incrementality improvements, measurement integrations), with clear goals, milestones, and success metrics aligned to Monetization outcomes and broader company OKRs.
Drive clarity through ambiguity in a complex technical domain: Convert vague problem statements into crisp program charters, decision points, and executable roadmaps; proactively identify gaps (requirements, ownership, resourcing, data readiness) and close them.
Influence technical direction and tradeoffs with strong technical judgment: Facilitate architecture/design alignment, surface core technical uncertainties early, and drive principled tradeoff decisions (accuracy vs. latency, experimentation rigor vs. speed, privacy constraints vs. measurement granularity).
Execute at both breadth and depth. At breadth by understanding the big picture, and at depth by being comfortable driving nitty gritty details with multiple teams.
Be a thought leader to your XFN stakeholders by influencing product roadmap during the annual & quarterly planning. Work cross functionally with engineering, product, design, data analytics, Sales, Business Development, Research, and product marketing to turn ambiguous opportunities into actionable outcomes.
Operate at Staff (IC16) scope and leadership altitude: Own the success of a strategic, complex program spanning multiple orgs; manage ambiguity across leadership levels; communicate program state, risks, and proposals (including tradeoffs) clearly to senior audiences (VP/Estaff/PLT as needed).
Build durable program mechanisms and best practices: Create repeatable operating rhythms (intake, prioritization, RAID, decision logs, launch criteria, post-launch learning loops), and scale execution through others (including other T/PgMs and functional leaders).
Use GenAI as the default operating model for EP PgM execution—producing AI-assisted first drafts of core program artifacts, modernizing high-toil workflows into AI-first mechanisms (e.g., intake triage, status synthesis, action/decision extraction, risk & dependency tracking), and synthesizing signals to proactively surface risks, decision/trade-offs, and escalation paths.
Prototype solutions to augment decisions through data (e.g. dashboards, data analysis) or simplify processes (e.g. process and workflow helpers, or internal tools) using AI coding assistants (“vibe coding”).
Follow Pinterest AI guidance for risk, governance, and safety-by-design: appropriately handle sensitive data, validate AI-generated outputs, document assumptions/limits, and ensure AI-assisted workflows meet applicable policy/compliance expectations before broad adoption.