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Technical Program Manager

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Remote

Technical Program Manager

Pinterest

Technical Program Manager

Skills

KafkaData AnalysisAICompliance

25 days ago

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Important information


Salary:

$103,965 – $214,044 / year

Location:

United States

Work mode:

Remote

Published on:

30 September 2026

What they need


Who you are

  • 2–4 years of TPM experience independently driving technical programs to completion, ideally within infrastructure, platform, or data-adjacent environments
  • Solid foundational understanding of distributed systems concepts — services, streaming pipelines, batch vs real-time processing
  • Strong execution and follow-through, with a track record of running multiple concurrent workstreams without dropping the ball
  • Comfortable working with data — building dashboards, tracking metrics, and turning progress into clear status updates
  • Excellent written and verbal communication, with experience managing cross-team dependencies and stakeholder expectations
  • Experience with ads, monetization, streaming systems (Flink/Kafka), or financial-controls processes is a plus; willingness to learn the domain is essential
  • 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 Computer Science, Engineering, a related field or equivalent experience

What the job involves

  • The Team:
  • Pinterest's Shopping & Delivery Infrastructure team builds and operates the catalog, indexing, retrieval, and serving systems that power Shopping and ads across every Pinterest surface, from search and homefeed to P2P and international markets
  • Our mission is to make Pinterest's shopping and delivery stack unified, scalable, and low-latency so we can drive sustainable revenue growth, exceptional Pinner experiences, and measurable advertiser outcomes
  • We're in the middle of a multi-year transformation of the stack, and we work closely with catalog, indexing, retrieval, serving, ads quality, and product teams to make Pinterest's shopping infrastructure faster, more reliable, and ready to scale
  • What You'll Do:
  • Independently drive a well-defined portfolio of Shopping catalog and indexing programs, keeping engineering owners, timelines, and dependencies on track
  • Run the day-to-day working-team cadence including standups, planning, decision-tracking, and documentation, so the team stays aligned on priorities and next steps
  • Build and maintain program dashboards and reporting that give engineering and cross-functional stakeholders a clear view of progress, risk, and decisions
  • Manage cross-team dependencies with partner teams across catalog, indexing, retrieval, serving, and ads quality
  • Communicate clearly in writing and verbally across
  • 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

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