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TemporalTemporalUnited States

Senior Engineering Manager, Compute

Lead and grow a high-ownership engineering team building and operating large-scale, multi-tenant compute platforms for frontier AI workloads. Own strategy, architecture, operations, capacity planning, and live-site reliability for next-generation compute infrastructure.

320k – 335k
Remote12+ YOEEngineering Management

About the role

Responsibilities

  • Own the strategy and standards of excellence for the compute layer that the world's agents run on, across design, delivery, and operations. Build a culture of ownership, quality, and customer-first decision-making.
  • Lead, hire, and grow a high-ownership team; roll up sleeves, ready to do deep into the trenches, by staying close to design docs and code, rather than managing from a distance. Coach engineers, level them up, and clear the friction that slows them down.
  • Drive the arc from today's compute toward the next-generation of compute platforms. Ground prioritization in customer and design-partner feedback, and turn ambiguous, fast-moving requirements into predictable, iterative delivery.
  • Own operations, run on-call and incident response, and drive blameless postmortems and the systemic fixes that prevent recurrence.
  • Guide the hard architectural decisions for large-scale, multi-tenant compute, where technical concerns cut across workload isolation and security, scheduling, fleet efficiency / utilization / goodput, and performance, while ensuring the platform is reliable and efficient for the workloads that depend on it.
  • Own utilization, capacity and supply planning, and the cost-per-unit-of-compute and margin profile of the fleet, across CPU compute today and accelerated compute ahead.
  • Partner with leadership, Product, SDK, UX/DX, Security, and design-partner customers to align priorities and unblock delivery. Communicate progress, tradeoffs, and risk clearly to technical and non-technical audiences alike.

Requirements

  • Proven experience leading software engineering teams that build and operate large-scale compute platforms or fleets, with strong operational practices.
  • 12+ years in software and/or infrastructure engineering, including 7+ years of people management and demonstrated ownership of delivery and live-site outcomes.
  • Deep distributed-systems and compute infrastructure depth, with the hands-on judgment to guide architecture and execution rather than from a distance.
  • Experience operating multi-tenant compute that other people's production workloads depend on.
  • Bachelor's degree in Computer Science or related field, or equivalent practical experience; advanced degree a plus.
  • Excellent communication skills, with the ability to partner across engineering, product, and leadership and fold customer feedback into the roadmap.
  • Strong leadership, coaching, and performance management; ability to grow engineers and build a healthy, accountable, high-ownership team.
  • Excellence in execution: planning, prioritization, and delivering iterative milestones in an ambiguous, fast-moving environment while managing unplanned work.
  • Fleet thinking: utilization, goodput, capacity and supply planning, and cost discipline as first-class engineering concerns.
  • Live-site reliability craft: on-call, incident management & response, and postmortem-driven continuous improvement.
  • Strong command of the building blocks of a compute platform: multi-tenant isolation and security, scheduling, and resource management.
  • Ability to review and raise the bar on technical artifacts (design docs, code reviews) across a distributed-systems codebase.

Nice-to-Haves

  • MicroVMs and virtualization (Firecracker, gVisor, Edera) or managed-compute primitives (AWS Fargate, GCP Cloud Run, AWS Lambda), and/or Kubernetes internals.
  • Building serverless or hosted-compute products from 0 to 1, including the rapid-delivery-vs-durable-platform tradeoffs that come with it.
  • Multi-cloud delivery across AWS and GCP.
  • Cold-start, warm-pool, and scheduling/latency optimization for on-demand compute.
  • Agent sandboxes, secure execution of untrusted code, or other AI-agent infrastructure.
  • GPU / accelerated compute: fractional GPUs (MIG, MPS, time-slicing), GPU scheduling, training vs. inference fleets, and multi-tenant GPU isolation.

Compensation & Benefits

  • Estimated pay range: $320,000 - $335,000.
  • Eligible to participate in Temporal's equity plan.
  • Unlimited PTO, 12 Holidays + 2 Floating Holidays.
  • 100% Premiums Coverage for Medical, Dental, and Vision.
  • AD&D, LT & ST Disability, and Life Insurance (Standard & Supplemental Available).
  • Empower 401K Plan.
  • Additional Perks for Learning & Development, Lifestyle Spending, In-Home Office Setup, Professional Memberships, WFH Meals, Internet Stipend and more!

Skills

Distributed SystemsCompute InfrastructureMulti-Tenant ComputeFleet ManagementCapacity PlanningIncident ManagementOn-CallPostmortemsMicrovmsVirtualizationKubernetesAWSGCPGpu SchedulingServerless
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