Founding Engineer - Site Reliability

Role Description

Reliability at uRun isn't a feature — it's the product. When model labs and production teams build on top of our inference platform, they are trusting us with their uptime, their latency, and their users. As our Site Reliability Engineer, you will own that trust end-to-end.

This is a founding SRE hire. You will define the reliability culture from scratch:

• The observability stack
• The incident response playbooks
• The SLOs
• The on-call process

You will work directly with infrastructure and platform engineers to close the gap between what we ship and what stays up.

What you'll actually be doing day-to-day:

• Define and own SLOs and error budgets across uRun's inference platform and supporting infrastructure
• Build and maintain the observability stack end-to-end: metrics, logging, tracing, and alerting across a distributed GPU compute environment
• Lead incident response: detection, triage, resolution, and blameless postmortems that drive lasting fixes
• Partner with ML infrastructure engineers to embed reliability into the deployment pipeline from day one
• Design and maintain runbooks, on-call rotations, and escalation paths as the team scales
• Drive capacity planning and traffic management across heterogeneous compute to protect latency and availability under load
• Identify and eliminate toil through automation, building systems that scale without scaling the team proportionally

Qualifications

• 7+ years in site reliability, production engineering, or infrastructure engineering in a high-availability, low-latency environment
• Deep experience owning SLOs, error budgets, and on-call processes in production at scale
• Strong observability background: you have built or owned monitoring stacks (Prometheus, Grafana, Datadog, or equivalent) and know what good alerting looks like
• Proven incident response experience: you have led real incidents under pressure and written postmortems that actually changed behaviour
• Hands-on with Kubernetes and cloud infrastructure (AWS preferred): you can debug a failing pod and a misconfigured VPC in the same afternoon
• Strong software engineering fundamentals: you write automation, not just runbooks
• Comfortable operating as the first and only SRE, setting standards without a template to follow

Requirements

• Experience supporting GPU compute or ML inference infrastructure in production
• Familiarity with stateful workloads, long-running sessions, or streaming inference systems
• Exposure to multi-tenant platforms where isolation, noisy neighbour problems, and billing-aware scheduling matter
• Prior founding or sole SRE experience at an early-stage company

Benefits

• Competitive salary and meaningful equity in an early-stage AI infrastructure company
• Health, dental, and vision — full coverage
• 401(k) — company-supported retirement savings
• FSA/HSA — flexible spending accounts for healthcare costs
• Paid time off — we trust you to manage your time
• Top-tier tooling — access to the best AI tools available: Claude, Codex, Kimi, and whatever else helps you move faster
• MacBook Pro and AirPods — the hardware you need, on us