Staff Site Reliability Engineer – Automation and Platform
Leads automation and platform engineering for ultra-reliable AI inference infrastructure, architecting self-service GitOps pipelines, observability, and tooling to eliminate toil across datacenters. Requires 8+ years SRE experience with large-scale clusters and tools like Argo CD and Prometheus.
About the job
Key Responsibilities
- Define and implement a robust strategy for delivering and running software reliably and at scale across multiple datacenters and cloud-based solutions.
- Architect self-service platforms and internal tooling that let product teams, external customers, and cluster operators safely trigger and observe critical workflows with minimal handoffs.
- Define and evolve reliability practices for inference workloads, including SLOs and SLIs for latency, throughput, and accuracy stability; error budgets; blameless postmortems; chaos testing; and capacity forecasting across multi-datacenter and on-prem environments.
- Mentor mid-level SREs, support critical incident escalations, and use production pain points to prioritize the highest-leverage automation work.
- Measure and drive impact through clear metrics, including toil reduction, deployment velocity, SLO compliance, MTTR, and adoption of self-service workflows.
Required Experience & Skills
- 8+ years in SRE, infrastructure engineering, or platform engineering, with a strong record of improving automation and reliability at large scale in FAANG, hyperscaler, or similarly demanding environments.
- Deep expertise operating large scale heterogenous clusters with a proprietary cloud control plane.
- Proven track record designing and delivering CI/CD or GitOps systems using Argo CD or similar tools, with strong safety and observability built in.
- Hands-on experience with observability systems such as Loki, Tempo, Mimir, and Prometheus.
- Ability to lead complex projects end to end, influence cross-functional stakeholders, and communicate technical direction clearly.
Nice-to-Haves
- Experience with Bazel or other large-scale build systems in production.
- Background in AI/ML inference systems, including model serving runtimes, GPU or wafer-scale orchestration, latency and accuracy SLOs, or drift monitoring.
- Prior work on predictive autoscaling, chaos engineering, or cost-aware capacity planning for compute-intensive workloads.
Skills
Argo Cd, GitOps, Prometheus, Loki, Tempo, Mimir, Bazel, CI/CD, SLOs, Chaos Engineering
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