Role Summary
Scale is building the agentic operating system that powers AI deployment across the world's most important organizations. The Platform PM is the person who determines what that foundation needs to be — and holds the bar on how well it gets built.
This is not a roadmap PM, a program manager, or a feature tracker. The Platform PM owns the core infrastructure that every FD team builds on top of: defining the foundation before anything else can be built reliably, sequencing work against real customer commitments and FD team velocity, identifying which FD-built patterns are ready to graduate to core, and ensuring that every capability that ships does so at a bar customers can trust without thinking about it.
The best Platform PMs have defined platform capabilities at production bar in high-stakes environments and understand the difference between what is necessary to build, what is interesting to build, and what should never be built at all.
What You'll Do
- Define the foundation. Determine what needs to be true at the core platform layer — across each capability pillar — before anything reliable can be built on top of it.
- Sequence it. Prioritize and order platform work given customer commitments, FD team velocity needs, and what is actually blocking progress today. Getting this wrong means building on an unstable base or building the right things in the wrong order and paying for it in rework and FD team drag.
- Identify patterns and graduate capabilities. Watch what FD teams are building across the application layer, determine what is genuinely repeating, and make the call on what moves to core — and when. Do not rush graduation or delay it out of caution.
- Hold the quality bar. Every capability on the platform roadmap earns its place twice: once by being necessary, and again by being done well enough that customers trust it without thinking about it. Keep the platform from becoming a graveyard of half-built capabilities.
- Unlock delivery team time to value. Forward deployed delivery teams should spend their time solving the hardest customer problems, not rebuilding plumbing on every engagement. That requires a platform that is secure by default, deployable anywhere, observable in production, and equipped with the agentic primitives, eval infrastructure, expert judgment capture, and data reasoning capabilities that every agent workload needs.
- Partner across the organization. Work closely with platform engineering, forward deployed PMs, and BU leads to surface signal, resolve sequencing tradeoffs, and keep the roadmap grounded in what is actually blocking work.
What We're Looking For
Must-Have Qualifications
- 6+ years in product management with meaningful time owning platform, infrastructure, or developer-facing products at production bar.
- 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.
- Strong sequencing judgment: can prioritize across competing customer commitments and team velocity needs with incomplete information, without thrashing.
- 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.
- 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.
Core Competencies
- 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.
- Sequencing and prioritization judgment: sequences work against real customer commitments and FD team velocity needs — not what is technically interesting or easiest to build.
- 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.
- 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.
- Cross-functional influence: drives field teams and platform engineering toward shared outcomes through evidence and framing, not process.
- Operating in ambiguity: creates structure where there is none; makes sequencing calls with incomplete information; does not wait for fully-formed requirements.
Nice-to-Haves
- 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.
Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.
Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$205,600—$300,000 USD
_PLEASE NOTE: _Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
_We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. _
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's _Know Your Rights poster_ for additional information.
_We comply with the United States Department of Labor's Pay Transparency provision. _
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