Senior Software Engineer, AI Platform

The Mission

For decades, progress in complex computer systems has relied primarily on human ingenuity. We are building an AI-powered systems engineer that helps experts design and optimize the next generation of computing infrastructure.

Our product goes far beyond a traditional assistant. It is a multi-agent system that reasons, experiments, and analyzes much like an experienced engineering team—turning weeks of manual systems research and optimization into hours of high-quality output.

Founded by accomplished systems researchers and engineers, our early-stage company is built on years of award-winning research. We are well funded by leading venture firms and technology executives, gaining traction with major customers, and expanding our engineering organization.

About the Role

We are hiring a Senior or Staff Software Engineer who combines strong software-engineering craft with genuine enthusiasm for AI.

We want engineers who embrace AI as a collaborator and are excited to build systems whose users include AI agents—not only humans.

You will own major parts of our product platform, work closely with the founders and our engineering and research teams, and help establish technical direction as the company scales. This is a hands-on role: you will spend most of your time designing, building, and operating systems yourself.

What You’ll Do
Own critical platform systems from design through production, including APIs, agent-workload orchestration and scheduling, deployment pipelines, and observability.
Establish foundational architecture and build shared infrastructure used across the company.
Keep the platform reliable, responsive, and cost-efficient as usage grows.
Own the developer experience, including the tools and workflows that help a small team ship quickly.
Collaborate with the founders and research team to turn research breakthroughs into dependable production systems.
Mentor engineers and raise the technical bar through thoughtful design and code reviews.
Build prototypes quickly, validate them, and iterate based on customer and user feedback.
What We’re Looking For

We are looking for engineers who have designed, built, and operated production systems—and developed the judgment that comes from doing so over time.

We are hiring at both the Senior and Staff levels. We generally expect at least five years of relevant experience for Senior candidates and eight years for Staff candidates. At the Staff level, you should have a track record of influencing technical direction beyond your own projects.

Strong signals include:

You have designed and operated large-scale distributed systems in production.
You have built platforms other engineers rely on, such as internal infrastructure, developer tools, control planes, or cloud services.
You have designed durable APIs used by other teams while evolving the underlying systems safely.
You have led a major migration—such as a datastore change, service decomposition, or replatforming—without disrupting the business.
You have improved systems by making them simpler, with fewer services, dependencies, or operational burdens.
You have built on Kubernetes APIs through controllers, operators, or schedulers—not only deployments.
You have shipped production systems using Go, TypeScript, or Python.
You have operated services on a major cloud platform using infrastructure-as-code tools such as Terraform.
You write clear design documents that explain tradeoffs and help teams reach sound decisions.
You have mentored engineers who went on to own critical systems independently.
You use AI tools in your engineering work and have informed opinions about where they help—and where they fall short.

Few candidates will have every qualification. If several describe you, we would like to hear from you.

Why Join Us?
Exceptional team: Work closely with recognized experts in AI, distributed systems, and infrastructure.
Meaningful technical impact: Help build technology that can dramatically accelerate difficult engineering research, design, performance, and cost-optimization work.
Strong foundation: Join a well-funded early-stage company backed by respected venture firms and technology leaders, with active customer engagements already underway.
Real ownership: Shape the platform, engineering culture, and technical direction while the team is still small.
Hard, consequential problems: Work on fundamental challenges at the intersection of AI quality, infrastructure performance, reliability, and cost.