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Senior AI Product Manager, Cybersecurity

Scale AI· Gen AI Product
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Hybrid (New York, NY), Hybrid (San Francisco, CA)$205.6k - $257kfull-timePosted 2mo ago

About the role

Senior AI Product Manager to build and own Scale's Cybersecurity portfolio, defining strategy, standards, and end-to-end execution for a new product line focused on vulnerability discovery, repro, patch generation, and security evaluation in AI systems.

Responsibilities

  • Own the roadmap and strategy for Scale's Cybersecurity portfolio across training data, RL environments, agentic task suites, and evaluation products — and stand the product line up end to end, from task taxonomy and sourcing through pricing and first external release.
  • Define the capability map we train and measure against: vulnerability discovery, proof-of-concept reproduction, patch generation and regression safety, secure code review, supply-chain analysis, malware and binary analysis, detection engineering, and incident triage.
  • Make the strategic call on where Scale competes across the offense–defense spectrum — which capabilities we build training data for, which we only measure, and which we decline.
  • Partner with ML researchers and security practitioners on task specifications, grader design, and verifiable rewards, holding to execution-grounded verification wherever possible.
  • Drive the infrastructure roadmap — reproducible vulnerability images, fuzzing and build toolchains, sandboxed execution, network-segmented ranges, automated verification — and build sourcing pipelines that scale past hand-curation.
  • Own the responsible-development posture: containment, coordinated disclosure for live vulnerabilities surfaced during task construction, need-to-know handling of sensitive artifacts, and customer vetting, working with Security, Legal, and Policy to make these processes real rather than nominal.
  • Establish governance for data quality, contamination prevention, license and IP hygiene, reproducibility, and release management.
  • Recruit and steward a contributor network of working practitioners — vulnerability researchers, exploit developers, malware analysts, detection engineers, incident responders — and design quality controls that hold up when reviewers are validating work at the edge of their own expertise.
  • Own external partnerships across open-source benchmark collaborations, academic security groups, and enterprise data partnerships.
  • Work directly with frontier labs and enterprise customers to understand where their models fail on security work, translate that into roadmap, and partner with GTM on launches and thought leadership.

Qualifications

  • Real cybersecurity work (vulnerability research, fuzzing and crash triage, reproducer development, patch/root-cause analysis, exploit development, malware analysis, red teaming, detection engineering, incident response)
  • 5+ years in product management, technical program management, consulting, or customer-facing technical roles (or equivalent practitioner depth with product ownership)
  • Working view of AI-for-security evaluation landscape (e.g., CyberGym, Cybench, CVE-Bench, BountyBench, CyberSecEval)
  • Software engineering depth to read unfamiliar code and reason about runtime behavior
  • Familiarity with post-training evaluation of models, agentic scaffolds, container-based rollout infrastructure
  • Excellent stakeholder management and executive communication skills
  • Sound judgment on dual-use questions and capability measurement for defenders
  • Entrepreneurial mindset and comfort in fast-moving, ambiguous environments

Skills

Required:Roadmap planningStakeholder managementSecurity domain knowledgeProduct management

Benefits

  • comprehensive health, dental and vision coverage
  • retirement benefits
  • learning and development stipend
  • generous PTO
  • commuter stipend (potential eligibility)
Last updated Aug 5, 2026. Interested? Apply on the company site.
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About Scale AI

Data-centric infrastructure to accelerate the development of AI

Scale accelerates the development of AI within organizations of any size to deliver critical business insights and operational efficiency. Its data-centric infrastructure platform leverages RLHF (Reinforced Learning with Human Feedback) to help organizations build the strongest AI models that supercharge their business, with customers across industries including Meta, Microsoft, U.S. Army, DoD’s Defense Innovation Unit, Open AI, General Motors, Toyota Research Institute, Brex, Instacart and Flexport.

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