Production Engineer, IaaS
Own observability, API surface, and control plane for a hyperscale AI compute fleet. Build production-grade data pipelines, stateful APIs, and Kubernetes infrastructure that other teams depend on.
Site Reliability Engineer
Builds and operates reliable, scalable AI infrastructure including observability, SLOs, incident response, automation, and performance tuning for ultra-low-latency serverless compute. Requires 3+ years SRE/DevOps experience with cloud, Kubernetes, programming (Go/Rust/Python), and observability tools.
175k – 250kSan Francisco, CADevOps / SREOnsite3+ YOE
About the role
Responsibilities
- Architect, operate, and continuously improve the core infrastructure powering our 25ms cold-start compute engine.
- Build and evolve our observability stack (metrics, traces, logs), ensuring we detect issues before users do.
- Define, monitor, and drive SLOs/SLIs across key system surfaces to maintain world-class reliability.
- Lead incident response with rigor: root cause analysis, post-mortems, and driving systemic fixes.
- Design and implement self-healing, automated operational systems to eliminate toil and scale ops.
- Work across compute, networking, storage, and sandboxed execution layers to tune performance under extreme workloads.
- Build automation and tooling—often with AI agents—to streamline operations, debugging, capacity planning, and failure prediction.
- Stress-test and push our systems to the edge: load testing, chaos engineering, and performance benchmarking.
- Own security best practices at the infrastructure layer, from sandboxed compute to network isolation.
- Partner with platform engineers to ensure reliability is designed into new features from day one.
Requirements
Required skills:
- 3+ years in SRE, DevOps, or infrastructure engineering roles
- Strong proficiency in at least one programming language such as Go, Rust, or Python
- Hands-on experience with a major cloud provider (AWS, GCP)
- Solid knowledge of Linux systems, networking fundamentals, and distributed systems
- Experience with bare-metal servers and datacenter operations (PXE/iPXE provisioning, IPMI/BMC, RAID/NVMe, SR-IOV, high-throughput networking)
- Experience with Kubernetes or similar orchestrators
- Familiarity with observability stacks (Prometheus, Grafana, ELK, Datadog)
- Experience building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins)
- Strong debugging, problem-solving, and incident-management skills
Preferred:
- Experience with infrastructure-as-code tools such as Terraform or Pulumi
- Knowledge of service mesh or API gateway technologies
- Exposure to chaos engineering or resiliency-testing frameworks
- Background in security best practices for cloud environments
- Prior experience in high-growth or high-availability environments
Bonus:
- Experience with serverless compute systems
- Sandboxed execution environments
- Ultra-low-latency runtime engineering
- Distributed key-value stores and databases
- Chaos engineering
- Rust, Go, or systems-level programming
- Deep generative AI infrastructure
Skills
KubernetesPrometheusGrafanaDatadogTerraformPulumiGoRustPythonAWSGCPLinuxCI/CDGitHub ActionsGitlab Ci
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