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Technical Program Manager, Platform

Scale AI

Technical Program Manager, Platform

full-timePosted: Jul 7, 2026Updated: Aug 29, 2026London, England, United Kingdom

Job Description

As a Technical Program Manager for the Platform team, you will partner with engineering teams to directly accelerate the development and maturity of the Scale Generative AI Platform (SGP). We are looking for a TPM who has actively built and shipped products in the past and understands how to deliver robust, scalable developer tooling and distributed systems. In this role, you will own the strategic alignment and end-to-end execution of our most critical infrastructure initiatives—from initial scoping to measurable, company-wide and customer-ready adoption. You will serve as the core communication backbone and connective tissue between platform engineering, product teams, and executive leadership. Operating in a hyper-growth, demanding AI environment, you will translate SGP’s architectural complexities into clear execution strategies, unblock engineering bottlenecks, proactively mitigate deployment risks, and ensure our foundational platforms deliver reliable, performant, and secure systems capable of global-scale deployment. Key Responsibilities Lifecycle & Platform Delivery: Lead strategic planning and high-velocity execution for SGP core capabilities (orchestration layers, model serving, APIs). Manage features from technical scoping and architecture design through production launch. Cross-Functional GenAI Alignment: Drive execution and manage complex technical dependencies across systems engineering, Core ML, Research, and Product teams to deliver unified SGP capabilities with architectural consistency. Technical Translation & Requirements: Translate complex infrastructure metrics (LLM inference optimization, GPU utilization, compute orchestration) into actionable roadmaps. Map demands like multi-tenancy, data privacy, and isolation into platform features. Risk & Dependency Mitigation: Proactively identify, track, and mitigate technical risks unique to massive-scale GenAI infrastructure and global SGP deployments, maintaining momentum despite fast-evolving AI frameworks. Developer Velocity & Operational Excellence: Establish lightweight agile processes that empower engineers to ship fast without breaking core systems. Define and enforce clear SLOs and performance benchmarks to guarantee production-grade reliability for clients. Metrics-Driven Adoption: Track and report on SGP adoption metrics, system reliability, delivery forecasts, and engineering bottlenecks directly to executive leadership to ensure the platform scales responsibly. Minimum Qualifications 5+ years of experience as a Technical Program Manager, Product Manager, or Software Engineer, with a proven track record of having built and shipped technical products or platforms from scratch (e.g., internal cloud infrastructure, developer APIs, distributed systems, or ML platforms). Platform Domain Expertise: 3+ years of dedicated experience managing programs focused directly on core engineering infrastructure, cloud-native ecosystems (AWS/GCP), container orchestration (Kubernetes), or distributed systems. AI/ML Infrastructure Literacy: Foundational understanding of the infrastructure required for the Generative AI lifecycle, including high-throughput data pipelines, GPU/CPU cluster utilization, or model training/evaluation setups. Masterful Communication: Proven track record of presenting to and influencing executive-level stakeholders, with the ability to translate complex technical/architectural challenges into clear business impacts. Execution Excellence: Advanced proficiency with iterative development methodologies and modern project management tooling (Linear, Jira, etc.) applied to foundational infrastructure environments. Nice-to-Have Qualifications Engineering Roots: Strong software engineering fundamentals, with prior professional experience as a Software Engineer, DevOps Engineer, or Data Developer before transitioning into program management. Platform Adoption Track Record: Proven success driving the internal adoption of technical platforms, SDKs, or APIs across disparate, fast-moving product lines. Data-Centric AI Familiarity: Direct experience working with large-scale data quality pipelines, distributed vector databases, or specialized AI inference engines (e.g., Triton, Ray). 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. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Locations

  • London, England, United Kingdom

Skills Required

  • iterative development methodologiesintermediate

Required Qualifications

  • 5+ years of experience as a Technical Program Manager, Product Manager, or Software Engineer, with a proven track record of having built and shipped technical products or platforms from scratch (e.g., internal cloud infrastructure, developer APIs, distributed systems, or ML platforms). (experience, 5 years)
  • Platform Domain Expertise: 3+ years of dedicated experience managing programs focused directly on core engineering infrastructure, cloud-native ecosystems (AWS/GCP), container orchestration (Kubernetes), or distributed systems. (experience, 3 years)
  • AI/ML Infrastructure Literacy: Foundational understanding of the infrastructure required for the Generative AI lifecycle, including high-throughput data pipelines, GPU/CPU cluster utilization, or model training/evaluation setups. (experience)
  • Masterful Communication: Proven track record of presenting to and influencing executive-level stakeholders, with the ability to translate complex technical/architectural challenges into clear business impacts. (degree)
  • Execution Excellence: Advanced proficiency with iterative development methodologies and modern project management tooling (Linear, Jira, etc.) applied to foundational infrastructure environments. (experience)

Preferred Qualifications

  • Engineering Roots: Strong software engineering fundamentals, with prior professional experience as a Software Engineer, DevOps Engineer, or Data Developer before transitioning into program management. (experience)
  • Platform Adoption Track Record: Proven success driving the internal adoption of technical platforms, SDKs, or APIs across disparate, fast-moving product lines. (experience)
  • Data-Centric AI Familiarity: Direct experience working with large-scale data quality pipelines, distributed vector databases, or specialized AI inference engines (e.g., Triton, Ray). (experience)
  • 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. (experience)

Responsibilities

  • Lifecycle & Platform Delivery: Lead strategic planning and high-velocity execution for SGP core capabilities (orchestration layers, model serving, APIs). Manage features from technical scoping and architecture design through production launch.
  • Cross-Functional GenAI Alignment: Drive execution and manage complex technical dependencies across systems engineering, Core ML, Research, and Product teams to deliver unified SGP capabilities with architectural consistency.
  • Technical Translation & Requirements: Translate complex infrastructure metrics (LLM inference optimization, GPU utilization, compute orchestration) into actionable roadmaps. Map demands like multi-tenancy, data privacy, and isolation into platform features.
  • Risk & Dependency Mitigation: Proactively identify, track, and mitigate technical risks unique to massive-scale GenAI infrastructure and global SGP deployments, maintaining momentum despite fast-evolving AI frameworks.
  • Developer Velocity & Operational Excellence: Establish lightweight agile processes that empower engineers to ship fast without breaking core systems. Define and enforce clear SLOs and performance benchmarks to guarantee production-grade reliability for clients.
  • Metrics-Driven Adoption: Track and report on SGP adoption metrics, system reliability, delivery forecasts, and engineering bottlenecks directly to executive leadership to ensure the platform scales responsibly.

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