Technical Program Manager, Platform

Scale AI Scale AI · Data AI · London, United Kingdom · Enterprise Engineering

Technical Program Manager for Scale Generative AI Platform (SGP) focusing on infrastructure initiatives like orchestration, model serving, and APIs. Requires experience building and shipping technical platforms, understanding of AI/ML infrastructure, and strong execution and communication skills.

What you'd actually do

  1. 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.
  2. Drive execution and manage complex technical dependencies across systems engineering, Core ML, Research, and Product teams to deliver unified SGP capabilities with architectural consistency.
  3. 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.
  4. Proactively identify, track, and mitigate technical risks unique to massive-scale GenAI infrastructure and global SGP deployments, maintaining momentum despite fast-evolving AI frameworks.
  5. 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.

Skills

Required

  • 5+ years of experience as a Technical Program Manager, Product Manager, or Software Engineer
  • 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

  • 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).

What the JD emphasized

  • built and shipped technical products or platforms from scratch
  • core engineering infrastructure
  • AI/ML Infrastructure Literacy
  • LLM inference optimization
  • GPU utilization
  • compute orchestration
  • massive-scale GenAI infrastructure

Other signals

  • building and shipping products
  • developer tooling
  • distributed systems
  • infrastructure initiatives
  • AI environment
  • architectural complexities
  • execution strategies
  • engineering bottlenecks
  • deployment risks
  • foundational platforms
  • global-scale deployment
  • orchestration layers
  • model serving
  • APIs
  • technical scoping
  • architecture design
  • production launch
  • Cross-Functional GenAI Alignment
  • systems engineering
  • Core ML
  • Research
  • Product teams
  • architectural consistency
  • infrastructure metrics
  • LLM inference optimization
  • GPU utilization
  • compute orchestration
  • multi-tenancy
  • data privacy
  • isolation
  • platform features
  • technical risks
  • massive-scale GenAI infrastructure
  • global SGP deployments
  • fast-evolving AI frameworks
  • Developer Velocity
  • Operational Excellence
  • agile processes
  • ship fast
  • SLOs
  • performance benchmarks
  • production-grade reliability
  • clients
  • Metrics-Driven Adoption
  • SGP adoption metrics
  • system reliability
  • delivery forecasts
  • engineering bottlenecks
  • executive leadership
  • platform scales responsibly
  • Technical Program Manager
  • Product Manager
  • Software Engineer
  • built and shipped technical products or platforms from scratch
  • internal cloud infrastructure
  • developer APIs
  • distributed systems
  • ML platforms
  • Platform Domain Expertise
  • managing programs focused directly on core engineering infrastructure
  • cloud-native ecosystems
  • container orchestration
  • Kubernetes
  • distributed systems
  • AI/ML Infrastructure Literacy
  • Generative AI lifecycle
  • high-throughput data pipelines
  • GPU/CPU cluster utilization
  • model training/evaluation setups
  • Masterful Communication
  • presenting to and influencing executive-level stakeholders
  • translate complex technical/architectural challenges into clear business impacts
  • Execution Excellence
  • iterative development methodologies
  • modern project management tooling
  • foundational infrastructure environments
  • Engineering Roots
  • software engineering fundamentals
  • Software Engineer
  • DevOps Engineer
  • Data Developer
  • program management
  • Platform Adoption Track Record
  • internal adoption of technical platforms
  • SDKs
  • APIs
  • disparate, fast-moving product lines
  • Data-Centric AI Familiarity
  • large-scale data quality pipelines
  • distributed vector databases
  • specialized AI inference engines
  • Triton
  • Ray
  • reliable AI systems
  • high-quality data
  • full-stack technologies
  • power the world's leading models
  • enterprises and governments build, deploy, and oversee AI applications
  • real impact