Runware is building high-performance infrastructure and products to power the worlds intelligence. Our platform enables developers and businesses to run fast, scalable inference across image, video and emerging modalities, while our Serverless platform allows customers to deploy and scale their own AI models on production-grade GPU infrastructure.
As a Site Reliability Engineer at Runware, you will help ensure these systems remain reliable, performant and resilient as we scale. This is a highly technical, hands-on role working across software, infrastructure and production operations to improve observability, reduce incidents, eliminate operational toil and build lasting improvements across complex distributed systems.
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
Requirements
- 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
- Experience operating high-throughput or low-latency APIs and distributed systems
- Experience with bare-metal infrastructure, GPU environments or AI and ML workloads
- Experience with RabbitMQ or other distributed messaging and queueing systems
- Experience operating MySQL, Redis, ClickHouse or similar production data systems
- Experience with global traffic management, load balancing, CDN platforms and hybrid infrastructure environments
- 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
Skills Required
- Strong experience operating and troubleshooting production systems at scale in SRE, Production Engineering, Platform Engineering or similar role.
- Strong understanding of distributed systems and debugging across applications, databases, queues, containers, networking and infrastructure.
- Experience designing and operating observability systems using metrics, logs and distributed tracing.
- Understanding of SRE principles including SLIs, SLOs, error budgets, capacity planning, incident management and reducing operational toil.
- Experience with Kubernetes, containers, Infrastructure-as-Code and automated deployment practices.
- Ability to write software and automation using languages such as Python, Go or PHP.
- Willingness to take strong ownership of production problems and participate in an engineering on-call rotation.
- Experience operating high-throughput or low-latency APIs and distributed systems.
- Experience with bare-metal infrastructure, GPU environments or AI/ML workloads.
- Experience with RabbitMQ or other distributed messaging and queueing systems.
- Experience operating MySQL, Redis, ClickHouse or similar production data systems.
- Experience with global traffic management, load balancing, CDN platforms and hybrid infrastructure environments.
- Experience building automated scaling, capacity management or self-healing systems.
What We Do
Runware delivers AI-as-a-Service at 5–10x lower cost and with higher speed than competitors. Built for scale, the service has already powered 4 billion+ creations for +100K developers and +250M end-users worldwide. Founded in 2023 and headquartered in San Francisco, Runware is backed by Insight Partners and a16z.
