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Temporal Technologies

Runs durable workflows for software applications

Director of Engineering - Compute

Full-Time
$214.4k - $351.8k/yr
Expert
Bachelor's, Master's
Remote in USA
Remote
Engineering ManagementEngineering Leadership

About the job

Requirements
  • Proven experience leading software engineering teams that build and operate large-scale compute platforms or fleets, with strong operational practices.
  • At least 15 years in software and/or infrastructure engineering, including at least 10 years of people management and demonstrated ownership of delivery and live-site outcomes.
  • Deep distributed-systems and compute infrastructure expertise, with the hands-on judgment to guide architecture and execution.
  • Experience operating multi-tenant compute that other people's production workloads depend on.
  • A bachelor's degree in Computer Science or a related field, or equivalent practical experience; an advanced degree is a plus.
  • Ability to partner across engineering, product, and leadership, communicate effectively, and incorporate customer feedback into the roadmap.
  • Strong leadership, coaching, and performance-management skills, with the ability to grow engineers and build a healthy, accountable, high-ownership team.
  • Ability to plan, prioritize, and deliver iterative milestones in an ambiguous, fast-moving environment while managing unplanned work.
  • Knowledge of fleet utilization, goodput, capacity and supply planning, and cost discipline as engineering concerns.
  • Expertise in live-site reliability practices, including on-call, incident management and response, and postmortem-driven continuous improvement.
  • Strong command of compute-platform building blocks, including multi-tenant isolation and security, scheduling, and resource management.
  • Ability to review and raise the bar on technical artifacts, including design documents and code reviews, across a distributed-systems codebase.
Responsibilities
  • Own the strategy and standards of excellence for the compute layer across design, delivery, and operations, and build a culture of ownership, quality, and customer-first decision-making.
  • Lead, hire, and grow a high-ownership team; stay close to design documents and code; coach engineers, develop their skills, and remove friction that slows them down.
  • Drive the evolution from current compute toward next-generation compute platforms, grounding prioritization in customer and design-partner feedback and turning ambiguous requirements into predictable, iterative delivery.
  • Own operations, run on-call and incident response, and drive blameless postmortems and systemic fixes that prevent recurrence.
  • Guide architectural decisions for large-scale, multi-tenant compute, addressing workload isolation and security, scheduling, fleet efficiency, utilization, goodput, and performance while ensuring reliability and efficiency.
  • Own utilization, capacity and supply planning, cost per unit of compute, and fleet margin across current CPU compute and future accelerated compute.
  • Partner with leadership, Product, SDK, UX/DX, Security, and design-partner customers to align priorities and unblock delivery; communicate progress, tradeoffs, and risks to technical and non-technical audiences.
Desired Qualifications
  • Experience with microVMs and virtualization, including Firecracker, gVisor, or Edera; managed-compute primitives such as AWS Fargate, GCP Cloud Run, or AWS Lambda; and/or Kubernetes internals.
  • Experience building serverless or hosted-compute products from 0 to 1, including balancing rapid delivery against durable-platform tradeoffs.
  • Experience with multi-cloud delivery across AWS and GCP.
  • Experience with cold-start, warm-pool, and scheduling or latency optimization for on-demand compute.
  • Experience with agent sandboxes, secure execution of untrusted code, or other AI-agent infrastructure.
  • Experience with GPU or accelerated compute, including fractional GPUs (MIG, MPS, time-slicing), GPU scheduling, training versus inference fleets, and multi-tenant GPU isolation.

About the company

Temporal Technologies develops a workflow execution platform for software teams building applications that span services and run over long periods. Developers define business processes as code, separating coordination logic from tasks such as API calls, payment processing and data transfers. The platform persists execution state and coordinates retries after failures, helping applications resume work without teams writing their own recovery infrastructure. Temporal maintains an open-source engine and sells Temporal Cloud, its managed service, with charges for actions, stored workflow history and support. Founded in 2019, the company is headquartered in Bellevue, Washington.

Company Size

501-1,000

Company Stage

Series E

Total Funding

$1.2B

Headquarters

Bellevue, Washington

Founded

2019

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Simplify's Take

What believers are saying

  • Learning has a budget: Temporal advertises up to $1,800 annually for professional enrichment, prorated.
  • Paid adoption expanded in September 2026: Temporal reported over 4,300 paying customers, up 139% annually.
  • Revenue momentum strengthened in September 2026: Temporal reported annualized revenue run-rate growth exceeding 200% year over year.

What critics are saying

  • Engineering carries on-call duties: Temporal says rotations are standard for most Engineering roles and select support teams.
  • Code evolution needs care: incompatible workflow changes produce nondeterminism errors, requiring a versioning strategy.
  • Cloud reliability has limits: published service commitments are 99.9% normally and 99.99% with high availability.

What makes Temporal Technologies unique

  • Workflows stay interactive: Temporal supports Signals, Queries and Updates while executions are running.
  • Language choice is broad: official SDKs include Go, Java, TypeScript, Python, .NET and PHP.
  • Source licensing is permissive: Temporal Server is published under the MIT license.

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Benefits

  • Unlimited Paid Time Off
  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Life Insurance
  • Disability Insurance
  • 401(k) Retirement Plan
  • 401(k) Company Match
  • Phone/Internet Stipend
  • Wellness Program
  • Professional Development Budget
  • Conference Attendance Budget

Growth & Insights and Company News

Headcount

6 month growth

1%

1 year growth

1%

2 year growth

-4%
TechDay
Oct 15th, 2026
Google Cloud & Temporal launch serverless workers.

Google Cloud & Temporal launch serverless workers. Fri, 16th Oct 2026 (Today) Google Cloud and Temporal have introduced Temporal Serverless Workers on Cloud Run, now in preview on Temporal Cloud. The offering lets developers run Temporal workers in Cloud Run worker pools that scale with activity in Temporal task queues. Temporal Cloud manages instance counts through the Cloud Run Admin API, while the worker code continues to run in the customer's own Google Cloud project, under the customer's service account and network settings. Temporal is an open-source execution platform for orchestrating distributed systems and AI agent workloads. Its workers poll for tasks rather than wait for incoming web requests, which has often pushed users towards Kubernetes clusters or virtual machines that stay provisioned even when queues are idle. Cloud Run worker pools are designed for background jobs without a public endpoint. In this setup, Temporal workers poll Temporal Cloud for tasks, and Temporal tracks queue conditions before adjusting worker pool size. Scaling model Temporal uses backlog-to-worker latency as its main scaling signal. When the delay between a task entering a queue and a worker picking it up crosses a threshold, the Temporal server notifies a worker controller, which adds capacity to the relevant worker pool. Scale-in is handled more cautiously. Temporal waits through a stabilisation period after the last time a task found no available worker, then reduces capacity in stages rather than cutting instance counts immediately. Instance counts remain within customer-defined minimum and maximum levels. If the first task after an idle period cannot tolerate startup delay, users can keep the minimum above zero. Otherwise, the platform can reduce the pool to zero when no work is pending. A central change is the removal of some workarounds previously needed to run Temporal workers on standard Cloud Run services. Those deployments typically required an HTTP listener, instance-based billing to keep CPU available between requests, and minimum instances to avoid scaling fully down. By contrast, worker pools have no public URL and do not require a load balancer. Google Cloud said they are priced at almost 40% less per vCPU-hour and GB-hour than instance-billed Cloud Run services, while also avoiding revision changes when only instance counts are adjusted. Version control The launch also addresses one of the more difficult aspects of operating Temporal workflows: updating worker code without disrupting running executions. Because Temporal workflows are stateful and deterministic, changing code mid-run can create non-determinism errors. To avoid that, the Cloud Run deployment model requires Temporal Worker Versioning. Each Worker Deployment Version runs as its own worker pool deployment, identified by a deployment name and build ID. Older versions can remain at zero instances until a workflow created on that version needs to run again. This allows workflows that started on one worker version to continue on that same version, while newer workflows are directed to a current or target deployment based on configuration. As older workflow executions drain away, the related worker pool can then be reduced to zero automatically. Two versioning behaviours are available. Under PINNED, a workflow stays on the build ID on which it started. Under AUTO_UPGRADE, a workflow moves to the new current or target Worker Deployment Version during rollout. The companies highlighted several use cases, including AI agents, long-running workflows and batch processing. In AI-related workloads, worker pools can scale up to handle bursts of model calls, embeddings or API activity, then scale down once queues empty. The configuration also supports attaching GPUs to workers, with those GPU-backed workers still able to scale to zero. For long-running workflows, the approach is intended to match uneven compute demand. A workflow may alternate between short tasks, long-running steps and periods of inactivity while waiting for external input from a person or another system. Batch jobs are another target. Since worker pools incur charges only while instances are running, organisations can leave a pool idle at zero between periodic runs such as billing cycles or media transcoding jobs, while using maximum instance limits to cap spend during peaks. Tampi Yellapragada, Product Manager at Google Cloud, wrote that the aim was to align Cloud Run worker pools with systems built around pull-based work rather than request-response patterns: "We built Cloud Run worker pools for exactly this kind of pull-based work: Your instances connect to a queue or stream, take the next item, and process it." He added: "Starting today, Temporal Cloud, which is the fully managed version of Temporal's open-source platform, can scale them for you."

Yahoo Finance
Oct 6th, 2026
Temporal acquires Oso team to build agent authorization after raising $550M

Temporal has acquired the team behind Oso to build agent authorisation into its execution platform. The move addresses a critical security challenge as AI agents gain access to business-critical systems and data. Research shows 96% of permissions go unused by human employees who exercise judgement, but agents lack this restraint. Temporal's platform already powers agents for OpenAI and Cursor, processing over 5 billion actions monthly across 500 namespaces at Netflix alone. The Oso team will help Temporal implement fine-grained access controls that survive the crashes and retries inherent in production environments. Graham Neray, Oso's founder, said agents' value and danger both stem from their system access, requiring precise developer controls. The announcement follows Temporal's September 2026 Series E funding round, which raised $550 million.

IntelPro
Sep 30th, 2026
Restate lands $20M as the need for durable infrastructure increases with AI agents.

Restate lands $20M as the need for durable infrastructure increases with AI agents. Instead of building its durable execution engine on top of an external database, the company developed its own storage, replication, and redundancy la When Stephan Ewen co-founded Restate in 2022 to provide durable workflow infrastructure, he couldn't have anticipated how valuable such an offering would become for managing AI agent processes. The Berlin-based startup had set out to build an execution engine that made multistep workflows resilient to crashes and network interruptions - something that made it a fit for the agentic era. "It never was built for agents in the beginning, but it just happened to be a perfect match for all these problems that agents surface," Ewen told TechCrunch. Ensuring durability is especially critical for agent workflows, which run longer and take inherently unpredictable paths compared to traditional software. "You need to make sure you track exactly what you do to make it reproducible and have a consistent outcome," Ewen said. The explosion of AI agents has provided a powerful tailwind for the startup. Over the last few months, Restate has closed multiple six- and seven-figure customer contracts, according to Ewen. That momentum has led Restate to secure a $20 million Series A led by Singular with participation from Redpoint Ventures and Capital One Ventures. The fresh capital will help Restate take on Temporal, the heavyweight in the durable infrastructure space. Temporal, which was founded in 2019, announced a $550 million Series E at a $12.55 billion valuation earlier this month. Despite being a much smaller provider of increasingly important technology, Restate has already managed to attract high-profile customers, including vibe-coding platform Replit. Instead of building its durable execution engine on top of an external database, the company developed its own storage, replication, and redundancy layers. This architecture allows Restate to be exceptionally fast and lightweight, Ewen said. Although many companies tend to use durability engines for so-called heavy-weight workflows, Restate is trying to change this with its more efficient and cost-effective system. Ewen said that in addition to providing durability for AI companies, the startup is serving Fortune 500 customers, including in the financial space. While Restate may be applied to different use cases, customers all have the same need - a way to ensure that if something fails mid-process, the system automatically finds a way to put itself back together, Ewen said. Prior to launching Restate, Ewen was a co-creator of a popular open source stream-processing framework, Apache Flink, and later became the CTO of Data Artisans, a company that was monetizing the project. Alibaba acquired Data Artisans in 2019 and rebranded it as Ververica, where Ewen continued to serve as CTO for three years. He co-founded Restate with former colleagues from Data Artisans and Ververica: Igal Shilman and Till Rohrmann. Ahmed Farghal, who was previously an engineer at Stripe and Meta, joined as the fourth co-founder at the Series A. The company intends to use its fresh capital to hire a go-to-market team, bring on more engineers, and expand its office in the San Francisco Bay Area to be closer to many of the current and potential customers. Nevertheless, Ewen insists that Restate's capabilities will soon be essential to companies outside of traditional tech companies. "If we fast-forward a couple of years, it's one of those tools, like a database, that I think pretty much any company will have a use case for, no matter their shape and size," he said.

Yahoo Finance
Sep 14th, 2026
Temporal raises $550M at $12.55B valuation as AI infrastructure demand surges

Temporal has raised $550 million in Series E funding at a $12.55 billion valuation, led by Lightspeed Venture Partners. Co-leads include Wellington Management, Growth Equity at Goldman Sachs Alternatives, and Tiger Global. The open-source platform, which powers AI applications, has seen significant growth in 2026. Its annualised revenue run rate recently surpassed $250 million, growing more than 200% year-over-year. Net dollar retention has exceeded 200% since February. Temporal Cloud processed 1.9 trillion actions in August, up more than 350% year-over-year. Open-source installs surpassed 43 million in August, up 134% since January 2026. The company now has more than 4,300 paying customers, including OpenAI, Snap, NVIDIA, Netflix, and JPMorgan Chase. Temporal provides infrastructure for reliable execution of critical applications, from payments to autonomous AI agents.

Temporal
Sep 14th, 2026
Temporal raises $550M at a $12.55B valuation as demand grows for reliable AI infrastructure

AI is raising the bar for reliability. See why Temporal's $550M Series E, backed by Lightspeed and others, is built to meet that demand.