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# Sr/Staff Infrastructure Engineer - Perm - Relocate to SF

- **Company:** Arc Full-time
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $250,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Audit Trail, Microsoft Azure, Continuous Integration, Customer Data Management, Software Debugging, DevOps, Disaster Recovery, Failover, Github, Pulumi, Google Cloud, Large Language Models, Backend, Kubernetes, Front End Software Development, Terraform, Docker
- **Published:** October 13, 2026
- **Apply:** https://arc.dev/signup?userType=developer&publicRandomKey=pre7jrge3k&to=https%3A%2F%2Farc.dev%2Fdashboard%2Fd%2Fverified-jobs%2Fpre7jrge3k%2Fapplication

## About the Role

* 5+ years in infrastructure, platform, SRE or DevOps engineering
 * Deep Kubernetes knowledge beyond deploying workloads: how clusters behave, fail and recover
 * Production experience with infrastructure as code (Pulumi or Terraform), Docker and GitHub Actions in multi-cluster, multi-region setups
 * A failure-first mindset: you design for what happens after something breaks
 * An understanding of how compliance, legal and customer contract requirements become engineering constraints
 * Enough full-stack range to debug across the stack, and the persistence to go several layers deep for the real root cause, * Care more about impact than about elegant solutions, and reach for the pragmatic 80/20 answer
 * Are resourceful and act with urgency
 * Enjoy early-stage building (startup experience is a plus, not a requirement)

## Description

You'll own the platform the whole company runs on. That covers how clusters are built and operated, how code reaches production, how customer data stays secure, and how the team knows the system is healthy. This is a build role, not maintenance, and you'll work day to day with product engineers. If you're curious about how LLM workloads change infrastructure design, you'll have plenty of room to experiment.

What you'll do

 * Design and operate Kubernetes across multiple clusters, regions and clouds (AWS, GCP, Azure), with failover and disaster recovery that hold up in a real outage
 * Build internal tooling so creating and managing environments is consistent from a laptop to production
 * Set up separate runtime strategies for ML and API workloads, balancing cost, performance and reliability without over-engineering
 * Build in security that customers trust and engineers barely notice: access control, workload identity, secrets, data residency and audit logging
 * Define SLOs and SLIs the team can actually hold to, with alerting that only fires when something truly needs attention
 * Own CI/CD on GitHub Actions and infrastructure as code in Pulumi
 * Keep Docker environments consistent across dev, staging and production
 * Find hard bugs anywhere in the stack, frontend and backend included, not just in the infrastructure
 * Speed up engineering: faster builds, cleaner environments, and automation for anything done more than twice
 * Own observability and uptime
 * Lead incident response and write postmortems the team learns from