Temporal powers durable execution for the world’s most demanding AI and enterprise systems. The Compute team at Temporal makes that durability feel effortless by building the managed compute primitives that run workers and other execution systems across Temporal Cloud.
We’re solving a hard platform problem: make compute transparent, elastic, safe-by-default, observable, and multi-cloud — without turning customers into infrastructure operators. We build platform primitives that span a variety of execution environments (e.g., serverless-style runtimes, containerized fleets, and customer-controlled deployments). Our work sits at the intersection of control plane + data plane: scaling decisions, isolation boundaries, multi-tenant safety, and production-grade observability. If you’ve built autoscaling systems, multi-tenant platforms, or cloud infrastructure, you’ll find a lot to love here.
See the "Compute team" link to read more --> Compute team
Invent
Create new managed compute primitives that feel first-class in Temporal Cloud: crisp abstractions, clean APIs, and an extension story across compute providers.
Design self-optimizing autoscaling systems (signals, backstops, debouncing, guardrails) that scale worker fleets safely and predictably.
Define the Open Source Server ↔ Cloud boundary for compute capabilities, keeping the architecture cohesive and maintainable.
Own
Architect, build, and operate services on the hot path of task execution where performance and correctness are customer-visible.
Deliver real-world cloud integrations (e.g., customer-account execution): IAM boundaries, secure credentials handling, networking constraints, quotas, and failure modes.
Make operability a feature: SLOs, tracing/metrics, load and failure testing, incident reviews, and continuous hardening.
Ship end-to-end: API design, rollout strategy, backwards compatibility, and long-term maintenance.
Teach
Raise the bar through design docs, strong reviews, pragmatic technical leadership, and mentorship.
Lead through influence across teams (Server, SDKs, Security, Control Plane) to land coherent platform changes.
Significant experience building distributed systems or multi-tenant platform services (design, implementation, and production operations).
Strong systems fundamentals: concurrency, performance, reliability, and failure-mode thinking.
A record of shipping platform primitives used by other engineers/customers (APIs, control planes, data planes).
Comfort owning outcomes: SLOs, incident response, and improving on-call quality over time.
Excellent written communication and crisp trade-off thinking. (Go experience is a plus; judgment matters most.)
Experience building cloud compute platforms spanning physical servers, CPU/GPU resources, virtual machines, container orchestration, and networking.
Experience extending Kubernetes through custom controllers and CRDs, and operating heterogeneous Kubernetes worker fleets.
Experience with IAM/security boundaries for cross-account execution models.
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