About the role
THE MISSION Nolla is building AI doctors so that top-quality healthcare is accessible to everyone. Nolla Skin is the #1 medical skincare treatment app in the U.S. App Store. We've treated thousands of acne patients in the U.S., scanned 1% of Norway's population for skin cancer, and our in-house clinical models are state of the art on clinical benchmarks. We just launched NollaMD, our urgent care app, and we're building dedicated specialty apps for conditions like birth control and allergies. We raised a $4.5M seed from General Catalyst.
THE ROLE This is an AI engineering role, not an ML engineering role. You won't be training models (unless you want to). You will wire LLMs and other custom models into production systems where the cost of getting it wrong is high, build the eval infrastructure that tells us when we're getting it right, and ship the backend surface area that keeps the product moving. You'll work directly with the founding team and your work reaches patients immediately. WHAT YOU'LL BUILD App Backends Build and maintain backends for our existing apps, plus stand up new ones as we launch new specialty apps Own backend systems end to end, from schema design to production Clinician Tooling Build the clinician-facing dashboards and tooling our medical team uses to review AI output Develop internal tools that clinical ops and physicians use daily AI Systems Work on prompts, tool calling, and inference optimization for the AI features in our apps Build evals and observability that give us confidence in what we deploy. You'll define what "good" looks like for our AI systems Implement abstention, routing, and fallback strategies that favor safety and correctness Jack-of-all-Trades Surface Area Support a wide range of work: payments, user flows, clinical infra, model deployment Help architect systems that support rapid product expansion: new verticals, new states, new clinical modalities WHAT YOU BRING 4+ years of backend, platform, or product engineering experience You ship your own things. You have a portfolio: side projects, open source, apps you launched You've worked on small teams and built things from zero Comfortable with the AI engineering toolkit: prompts, evals, tool calling, RAG, common LLM APIs. You have opinions on when each tool is the right one Strong product instincts: you don't need a PM to tell you what to build, you can scope and ship Strong TypeScript and Python
