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Runware

Senior Site Reliability Engineer

RemoteUnited Kingdom only
Published
Role
SRE
Experience
Senior
Employment
Full-time
Salary not disclosed
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Open to GB only. Set where you work from to check your eligibility.

No BS summary

Senior SRE for production-scale distributed systems, Kubernetes/containers, IaC, observability, and automation. Must be in the United Kingdom or otherwise employable there, comfortable with on-call and debugging APIs, databases, queues, networking, infrastructure, and GPU-backed workloads.

Core skills

KubernetesObservabilityAutomation

Required skills

ContainersIaCPython/Go/PHP

Optional skills

RabbitMQMySQLRedisClickHouseCDN platforms

What you'll do

  • Own and improve the reliability, availability and performance of critical production services across the Runware platform
  • Define and evolve our reliability practices, including SLIs, SLOs, alerting, observability and production-readiness standards
  • Investigate complex production issues across distributed systems, APIs, networking, queues, databases and GPU-backed workloads, participating in our engineering on-call rotation
  • Lead and contribute to incident reviews and RCAs, turning recurring failure modes into lasting engineering improvements
  • Reduce operational toil through automation, automated remediation and improvements to deployment safety, recovery and system resilience
  • Work closely with Engineering and DevOps teams on capacity planning, performance, scaling and architectural improvements as the platform grows

What they require

  • Have strong experience operating and troubleshooting production systems at scale in an SRE, Production Engineering, Platform Engineering or similar role
  • Have a strong understanding of distributed systems and are comfortable debugging across applications, databases, queues, containers, networking and infrastructure
  • Have experience designing and operating observability systems using metrics, logs and distributed tracing
  • Understand SRE principles including SLIs, SLOs, error budgets, capacity planning, incident management and reducing operational toil
  • Have experience with Kubernetes, containers, IaC and automated deployment practices, alongside the ability to write software and automation using languages such as Python, Go or PHP
  • Take strong ownership of production problems and are comfortable participating in an engineering on-call rotation, taking issues from initial investigation through to long-term remediation
  • Preferred: Experience operating high-throughput or low-latency APIs and distributed systems
  • Preferred: Experience with bare-metal infrastructure, GPU environments or AI and ML workloads
  • Preferred: Experience with global traffic management, load balancing, CDN platforms and hybrid infrastructure environments
  • Preferred: Experience building automated scaling, capacity management or self-healing systems

Benefits

  • We’re a remote-first collective, meeting in person twice a year to plan, brainstorm, celebrate wins, and enjoy some face-to-face time.
  • We have core hours for cooperative working and calls, but outside of that your calendar is yours.
  • Work the hours that let you perform at your peak while also building a healthy life.
  • Our release cycles are fast and intense, but they’re followed by real downtime.
  • After big pushes we expect the team to unplug, recharge, and come back ready & stronger than ever for the next leap.
  • Generous paid time off – vacation, sick days, public holidays
  • Meaningful stock options – share in the upside you create
  • Remote-first setup – work from home anywhere we can employ you
  • Flexible hours – own your schedule outside core collaboration blocks
  • Family leave – paid maternity, paternity, and caregiver time
  • Company retreats – twice-yearly gatherings in inspiring locations

Runware is building high-performance infrastructure and products to power the worlds intelligence. The platform enables developers and businesses to run fast, scalable inference across image, video and emerging modalities, while its Serverless platform allows customers to deploy and scale their own AI models on production-grade GPU infrastructure.

AI InfrastructureStartup
Salary not disclosed