Software Engineer

You'll be a Full Stack Engineer who uses AI to build — and builds with AI. Two things at once: you ship real applications faster by treating LLMs as a team of junior developers you manage, and you build the AI use cases themselves — agents, RAG pipelines, LLM-powered products that work at scale. You'll work across the stack — cloud, backend, AI agents, frontend — and own what you build. We're building the Universal Electric Vehicle at Ford, doing things differently.

What You'll Do
Orchestrate agents to build. Use AI as your default way of working — agents do the heavy lifting, you direct, review, and harden. You set the bar for how the team builds with AI.
Build the AI use cases. Design and ship AI-powered applications and agents — RAG pipelines, LLM integrations, agentic workflows. Understand what's happening under the hood and make it work in production, at scale.
Ship cloud-native systems on GCP. Design, deploy, operate. You own the architecture, the infrastructure-as-code, and the CI/CD pipeline. No throwing code over the wall.
Connect systems that don't want to be connected. Build the integration layer across enterprise SaaS platforms. Expect messy APIs, legacy constraints, and creative problem-solving.
Automate what shouldn't be manual. If a human repeats it, you write the code — or point an agent at it — to stop it.
Make other engineers faster. Build the tools, agent workflows, and guardrails that remove friction. Developer productivity is a multiplier.

- BS in Computer Science, Electrical Engineering, or a related field. MS is a plus, not a substitute for shipping software.
- 2+ years building and deploying full-stack applications in production.
- 2+ years on cloud-native platforms (GCP preferred).
- Demonstrable experience building AI agents or applications — show us what you've built, not what you've read.