Founding Engineer - Full Stack

The Opportunity

Neuromorphic Labs is a Seed stage AI Startup, backed by top-tier VCs. We are hiring for a founding engineer at at the Staff and Senior level. This is a rare kind of role. You will own major parts of the platform from early stages, and play a part in building out the company itself: how we build, how we work together, and what we value as an organization.

We are building a high-trust, high-standards team of exceptional builders who want to move fast, go deep, own outcomes, invent better ways to create unmistakable customer value and ultimately drive business and personal success.

Our mission is to enable every organization to own its AI future.

As intelligence becomes something companies build, own, and continuously improve, models, data, agents, and AI systems are becoming a new strategic moat. But production AI is still too fragmented, complex, and difficult to trust.

We are building the trust layer for production AI, a foundational platform that makes security, governance, and control intrinsic to every model, artifact, and deployment, so organizations can move faster and scale AI with confidence.

You are building the thing, not inheriting it. As a founding engineer, you will make the architectural decisions everything else gets built on: the core platform, the technology stack, and the engineering culture. There is no legacy codebase and no committee.

The equity is real. The pace of progress in AI has created a once-in-a-lifetime window, and where you spend the next few years matters more than it ever has. You can spend them at a big tech where you are a line item in a headcount plan, doing your best work under the constant pressure of the next layoff cycle while someone else captures the upside.

Or you can spend them as a founding engineer with meaningful equity in what you build.

You will work directly with a founder who has done this  CEO has nearly two decades of experience building and scaling AI infrastructure businesses. He scaled a business from about $100M into a multi-billion-dollar segment at a leading cloud provider, and served as Chief Product Officer of a company he helped take public, now valued at over $50B. He leads by example, stays hands-on, and invests heavily in developing people and helping them do the best work of their careers.

The timing is now. Enterprise AI is crossing from experimentation into production right now, and the infrastructure layer underneath it is being decided. The companies that define that layer will be built in the next few years, by small teams that move fast.

This is a hands-on building role. You will report to the CEO and collaborate closely with our founding Product Architect on the product platform. We expect roughly 80% of your time on product development, with the rest split between product research and direct customer support.

• Design, build, test, and operate production-grade features and services.

• Build and run systems that deploy across public cloud, on-prem, and hybrid environments.

• Contribute to architecture and technical decisions, partnering with the Product Architects on the bets that shape the platform.

• Take part in product research: prototyping new approaches and evaluating emerging tools and techniques.

• Work directly with early customers to turn real-world requirements into working capabilities and to support them in production.

• Use AI-driven development workflows (Claude Code, Cursor, or equivalent) as a daily multiplier on velocity and quality.

• Help set the bar for engineering quality and craft as the team grows.

We are hiring across Senior (L5 equivalent) and Staff (L6 equivalent) levels. The work is the same. The difference is depth of experience and the scope of the systems you have built and owned.

• 5+ years of hands-on engineering experience building and shipping production software, with a track record of maintaining it in production.

• Experience building distributed systems, backend services, or infrastructure platforms with an eye for reliability and performance.

• Working knowledge of cloud-native technologies:
  Kubernetes, containerized…