Sr. Technical Program Manager, Personalization

Pinterest•San Francisco, CA

12d•Remote

About The Position

Pinterest is looking for a Senior Technical Program Manager, Personalization to join their Experience & Personalization (P13N) organization. This role will focus on driving programs that power personalization systems and experiences, making Pinterest feel uniquely tailored to each user. The role involves working across Relevance/ML, product surfaces (Homefeed, Explore, Boards, Shopping), and platform teams. Pinterest emphasizes the use of AI as a partner in creativity and impact, and candidates are expected to be comfortable explaining their approach and how they collaborate with AI. The interview process will explore foundational skills and AI collaboration. Technical Program Managers at Pinterest are described as proactive owners with deep program craft and technical fluency, serving as trusted partners to Product, Engineering, and Data Science.

Requirements

5+ years of experience as a Technical Program Manager (or similar role) driving complex, cross-functional technical programs.
Experience working with personalization, recommendations, relevance, or similar ML/AI-driven systems in consumer products (e.g., feeds, search, ranking, discovery).
Demonstrated ability to take ambiguous personalization problem spaces (e.g., “make the experience more anticipatory,” “optimize for long-term value”) and turn them into clear, actionable roadmaps and execution plans.
Strong program management fundamentals: highly organized, comfortable managing multiple complex workstreams, and skilled at building governance, planning, and communication structures that scale.
Data-driven decision-maker who is comfortable partnering with Data Science on experiment design, interpreting results, and using metrics (engagement, retention, revisitation, latency) to guide priorities and tradeoffs.
Excellent written and verbal communication skills, with a track record of explaining nuanced, technical topics to both technical and non-technical stakeholders, including senior leadership.
Proven ability to influence and align cross-functional partners in situations with competing priorities or unclear ownership, especially across product surfaces and platform/ML teams.
Experience creating or evolving processes and playbooks that improve how teams plan, execute, and review personalization work at scale.
AI-first execution mindset and workflow design fluency —comfortable using GenAI to accelerate TPM work, “vibe-coding” small helpers with AI coding assistants, and operating within AI governance and safety-by-design expectations.
Bachelor’s degree in a relevant field such as computer science, computer and information technology, or equivalent experience.

Responsibilities

Own a portfolio of personalization programs that span recommendation platforms, ranking and optimization strategies, and new anticipatory experiences (e.g., unified landing pages, intelligent/AI-generated boards), with clear goals, milestones, and success metrics.
Drive cross-surface execution so that personalization improvements can scale efficiently across multiple experiences (e.g., Homefeed, Explore, SEO landing pages, board and shopping surfaces), working closely with product and engineering owners in each area.
Partner with Relevance and Data Science to ensure our ranking and modeling work prioritizes long-term value and revisitation (not just short-term clicks), and that experiment learnings systematically inform future roadmap and investment decisions.
Design and run the operating model for personalization —creating cadences, dashboards, and decision forums that give leaders and teams a clear view of program health, risks, dependencies, and tradeoffs across the personalization portfolio.
Align stakeholders across organizations (Relevance/ML, product surfaces, infra, curation, growth) when there are competing priorities or ambiguous ownership, and drive crisp, data-backed decisions that keep the personalization roadmap moving.
Communicate complex work simply, turning deeply technical modeling and platform efforts into clear narratives about impact on Pinners (discovery quality, relevance, anticipatory experiences) and on the business (engagement, retention, revisitation).
Use GenAI as a default PgM tool —starting from AI-assisted drafts for core artifacts (charters, plans, status, decision memos) and redesigning high-toil PgM workflows (status synthesis, RAID tracking, intake triage) into AI-first mechanisms where it’s safe and effective to do so.
Prototype lightweight AI-assisted helpers (e.g., scripts, dashboards, workflow tools) with AI coding assistants to make it easier to understand personalization experiments, surface-level performance, and program health—while adhering to Pinterest’s AI governance and safety-by-design expectations.