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Site Reliability Engineer

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Strobe Power Corporation
Full Time position
Listed on 2026-10-18
Job specializations:
  • IT/Tech
    Cloud Computing: Infrastructure & Operations, Network Engineer, Systems Engineer, SRE/Site Reliability
Salary/Wage Range or Industry Benchmark: 140000 - 210000 USD Yearly USD 140000.00 210000.00 YEAR
Job Description & How to Apply Below

Strobe is building the world's largest power plant: not a single site, but a distributed fleet of buildings, batteries, EVs, and generators that buy and sell power in real time across wholesale energy markets.

Keep a fleet of power plants online. Own reliability across the cloud platform, the control room, and the hardware in the field, for systems where downtime means missed grid events and real dollars.

What you'd own
  • Uptime and latency of the dispatch path, from the cloud decision to the command on site
  • Observability: metrics, logs, and alerts that page on real impact and nothing else
  • On-call, incident response, and postmortems for systems that control physical equipment
  • AWS infrastructure as code (Terraform), CI/CD, and safe deploys
  • Edge fleet reliability: connectivity, OTA updates, and remote diagnostics (balena, containerized runtimes)
  • Network links to utilities and grid operators (VPNs, tunnels, DNP3) and how they fail
  • Capacity, cost, and resilience of the data and control platforms
Strong fit if you have
  • Production SRE or infrastructure experience on AWS
  • Terraform at scale (modules, remote state, multi-workspace patterns)
  • Strong Linux, networking, and debugging fundamentals
  • Alerting and on-call that people trust, because you built it
  • Python, Rust, or Go for tooling
Bonus points
  • Edge or IoT fleets, industrial protocols, or OT networks
  • Site connectivity: SD-WAN, VPNs, cellular failover
  • Energy or other safety-critical, real-time systems

Stack: AWS / Terraform / Python / Rust / balena / Grafana / DNP3 / Modbus. AI-agent-native monorepo with deep investment in agent-enabled engineering efficiency.

Small team, high ownership, no layers.

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