Senior Software Engineer - Devops & Platform, AI Systems

Who You Are

A software engineer who chose infrastructure. You write real code - not just glue scripts. You'd be dangerous on a product team, but you'd rather build the systems that make every product team faster. Platforms, not tickets.

An agent orchestrator, not a typist. You don't want to be a faster keyboard. You manage agents to do the heavy lifting - generating IaC, triaging alerts, writing the first draft of the runbook - while you keep your hands on the architecture and the judgment calls. The terminal is a cockpit for orchestration.

Productively lazy. Your instinct is to eliminate toil at the root. If a human is clicking through a console or babysitting a deploy, you replace them with code or an agent. Your biggest bottleneck should be deciding what to automate next - while the automation runs itself.

Fundamentals first. Linux, networking, distributed systems, how things actually fail under load. You understand the machine, not just the tool that wraps it. When the pipeline breaks at 2am, you can read the trace and fix the cause - and when an agent proposes a fix, you can tell whether it's right.

First-principles thinker with vision. You design for the failure mode, not the happy path. You question the assumptions, simplify the system, and build for the next order of magnitude - not just today's load.

High agency. You don't wait for perfect specs or permission. You find a path, propose it, and move. Large organizations have walls; you figure out which ones to go through, around, or remove - and you do it constructively.

I'm looking for a "lazy" engineer. Not lazy about reliability - lazy about toil. If you'd rather automate a thing once than do it by hand ten times, if a manual deploy or a copy-pasted runbook makes you physically ill, you belong here. This is a DevOps and platform role for someone who is a serious software engineer first. You won't just keep the lights on - you'll write the code that makes the lights keep themselves on. You'll build the platform, the pipelines, and the agent-driven automation that lets the whole team ship AI applications fast and safely. We're building the Universal Electric Vehicle at Ford, doing things differently. If you already live in 2030, keep reading.

What You'll Do

• Build the platform. Design and operate the cloud-native foundation on GCP - compute, networking, observability, and the golden paths other teams build on.

• Automate everything that shouldn't be manual. Infrastructure-as-code, self-service pipelines, auto-remediation. If a human repeats it, you write the code - or point an agent at it - to stop it.

• Orchestrate agents for ops. Use AI to draft IaC, generate tests, triage incidents, and summarize signal from noise. You direct, review, and harden - agents do the grunt work.

• Own CI/CD end to end. Fast, reliable, reproducible delivery. Build the pipelines that let engineers ship multiple times a day with confidence.

• Engineer reliability in. SLOs, monitoring, alerting that means something, and incident response that gets calmer every quarter. Make on-call boring.

• Secure the path. Bake security and compliance into the platform so doing the right thing is the easy thing - secrets management, least privilege, supply-chain hygiene.

• Support AI workloads. Build the infrastructure that runs LLM and agentic systems in production - scaling, cost control, and the deployment patterns AI apps actually need.

What You'll Do

• Build the platform. Design and operate the cloud-native foundation on GCP - compute, networking, observability, and the golden paths other teams build on.

• Automate everything that shouldn't be manual. Infrastructure-as-code, self-service pipelines, auto-remediation. If a human repeats it, you write the code - or point an agent at it - to stop it.

• Orchestrate agents for ops. Use AI to draft IaC, generate tests, triage incidents, and summarize signal from noise. You direct, review, and harden - agents do the grunt work.

• Own CI/CD end to end. Fast, reliable, reproducible delivery. Build the pipelines that let engineers ship multiple times a day with confidence.

• Engineer reliability in. SLOs, monitoring, alerting that means something, and incident response that gets calmer every quarter. Make on-call boring.

• Secure the path. Bake security and compliance into the platform so doing the right thing is the easy thing - secrets management, least privilege, supply-chain hygiene.

• Support AI workloads. Build the infrastructure that runs LLM and agentic systems in production - scaling, cost control, and the deployment patterns AI apps actually need.