Manager II, Technical Program Management - Platforms

What you’ll do

• 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.
• Lead a portfolio of complex, cross-functional technical programs across Quality Engineering, Client Foundations, and Ads & Core Infrastructure.
• Partner with engineering leaders to define program outcomes, establish execution plans, manage dependencies and risks, and drive delivery against multi-quarter goals.
• Build and run an integrated operating cadence across the portfolio, including roadmap planning, milestones, decision forums, status updates, and escalation paths.
• Drive programs that improve software quality, engineering hygiene, release confidence, reliability, and developer productivity across foundational platform investments. This includes areas such as code coverage, bug and incident SLAs, release quality, and platform modernization.
• Lead technical program management for client foundations modernization across iOS, Android, and Web, helping improve testability, maintainability, developer workflows, and safe release practices.
• Drive foundational programs across Ads and Core Infrastructure, including modernization, reliability improvements, platform simplification, and better execution across shared infrastructure and APIs. The related portfolio includes initiatives such as search/discovery infrastructure modernization, ingestion and catalog unification, media pipelines, and developer productivity improvements.
• Manage and develop a small TPM team while remaining hands-on with the most strategic or highest-risk programs.

What we’re looking for

• 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.
• Significant experience leading large, cross-team technical programs in ambiguous environments with complex technical and organizational dependencies.
• Experience translating strategy and organizational goals into a clear multi-quarter roadmap with milestones, dependencies, and measurable outcomes.
• Strong execution discipline, including risk management, governance, dependency tracking, and driving accountability across multiple teams.
• Strong communication and stakeholder management skills, including the ability to frame tradeoffs, drive alignment, and communicate crisply with senior technical leaders.
• Technical fluency across platform and infrastructure domains such as distributed systems, APIs, reliability/observability, developer tooling, client platforms, or data/infrastructure systems.
• Experience driving modernization, quality, or platform transformation efforts that improve reliability, speed, productivity, or software quality.
• People leadership experience, including coaching, setting direction, and growing team capability over time.
• Bachelor’s degree in Computer Science, Engineering, a related field or equivalent experience.