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Product Manager (Enterprise Core Platform)

Scale AI · San Francisco, United States

External listingfull-time2 months ago

About The Role

Join Scale, a leading company in AI deployment. As a Product Manager for the Enterprise Core Platform, you will define the foundation of our platform, prioritize and sequence work, identify patterns, and ensure quality. You will work closely with platform engineering, forward deployed PMs, and BU leads. This role requires technical fluency, a strong record of defining and shipping platform capabilities, and the ability to operate in ambiguity.

  • Definir la base de la plataforma y determinar lo que debe ser cierto en la capa de plataforma central.
  • Priorizar y ordenar el trabajo de la plataforma en función de los compromisos con los clientes y las necesidades de velocidad del equipo.
  • Identificar patrones y graduar capacidades, observando lo que los equipos de FD están construyendo y determinando qué se mueve al núcleo.
  • Technical fluency sufficient to hold real conversations with platform engineers about architectural tradeoffs across infra, auth, observability, deployment, and agent runtime. Not deep coding, but genuine comprehension of how production systems work
  • Demonstrated record of defining and shipping platform capabilities — not features on top of a platform someone else built. You can describe the architectural decisions you made, what production required, and what you learned
  • Extreme ownership and follow-through: closes loops without reminders, drives outcomes across teams without formal authority, holds self and others to commitments
  • Clear, precise communication: adjusts for audience (platform engineer vs. FD PM vs. executive); writes and speaks at the right level of detail
  • Strong sequencing judgment: can prioritize across competing customer commitments and team velocity needs with incomplete information, without thrashing
  • 6+ years in product management with meaningful time owning platform, infrastructure, or developer-facing products at production bar
  • Sequencing and prioritization judgment: sequences work against real customer commitments and FD team velocity needs — not what is technically interesting or easiest to build
  • Operating in ambiguity: creates structure where there is none; makes sequencing calls with incomplete information; does not wait for fully-formed requirements
  • Platform foundation ownership: has defined what a platform capability needs to be before it can be used reliably in production; understands what 'done' means at the platform layer vs. the application layer
  • Quality discipline: every capability earns its place twice — by being necessary and by being done well enough that it is trusted without thinking about it
  • Pattern recognition: identifies when field-built work has genuinely repeated and is ready to graduate to core; does not rush graduation or delay it out of caution
  • Cross-functional influence: drives field teams and platform engineering toward shared outcomes through evidence and framing, not process
  • Direct experience with AI/ML platform infrastructure — agent frameworks, eval pipelines, fine-tuning workflows, or observability for production AI systems
  • Experience deploying into constrained environments: government, regulated industries, air-gapped or classified infrastructure
  • Prior experience as a platform or infrastructure PM at a company where field-built patterns were a key signal source for the core product

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