Head of Engineering, Compute
Leads the engineering organization responsible for Temporal’s large-scale, multi-tenant compute platform, including architecture, reliability, fleet economics, capacity planning, and team growth. Requires 15+ years of software or infrastructure engineering experience and 10+ years of people management.
About the job
Responsibilities
- Set the strategy and standards of excellence for a large-scale compute platform across design, delivery, and operations.
- Lead, hire, coach, and grow a high-ownership engineering team while remaining close to design documents and code.
- Drive the evolution from current compute infrastructure to next-generation compute platforms.
- Prioritize work using customer and design-partner feedback and convert ambiguous requirements into predictable delivery.
- Own on-call operations, incident response, blameless postmortems, and systemic reliability improvements.
- Guide architecture for multi-tenant compute, including workload isolation and security, scheduling, fleet efficiency, utilization, goodput, and performance.
- Own utilization, capacity and supply planning, cost per unit of compute, and fleet margins across CPU and accelerated compute.
- Partner with engineering, product, SDK, UX/DX, security, leadership, and customers to align priorities and communicate tradeoffs and risks.
Requirements
- Experience leading software engineering teams that build and operate large-scale compute platforms or fleets.
- 15+ years of software and/or infrastructure engineering experience, including 10+ years of people management.
- Demonstrated ownership of delivery and live-site outcomes.
- Deep distributed-systems and compute-infrastructure expertise with hands-on architectural judgment.
- Experience operating multi-tenant compute supporting production workloads.
- Bachelor's degree in Computer Science or a related field, or equivalent practical experience.
- Strong communication, leadership, coaching, and performance-management skills.
- Experience with planning, prioritization, iterative execution, and managing unplanned work.
- Understanding of utilization, goodput, capacity and supply planning, and cost discipline.
- Expertise in on-call operations, incident management, incident response, and postmortem-driven improvement.
- Strong command of multi-tenant isolation and security, scheduling, and resource management.
- Ability to review and improve design documents, code reviews, and distributed-systems code.
Nice to Have
- MicroVMs and virtualization, including Firecracker, gVisor, or Edera.
- Managed-compute primitives such as AWS Fargate, Google Cloud Run, or AWS Lambda.
- Kubernetes internals.
- Building serverless or hosted-compute products from 0 to 1.
- Multi-cloud delivery across AWS and Google Cloud.
- Cold-start, warm-pool, and scheduling/latency optimization for on-demand compute.
- Agent sandboxes, secure execution of untrusted code, or AI-agent infrastructure.
- GPU and accelerated compute, including fractional GPUs, MIG, MPS, time-slicing, GPU scheduling, training and inference fleets, and multi-tenant GPU isolation.
Skills
Distributed Systems, Compute Infrastructure, Kubernetes, AWS, GCP, Firecracker, Gvisor, Edera, Aws Fargate, Google Cloud Run, AWS Lambda, Gpu Scheduling, Multi-Tenant Isolation, Incident Response
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