Director of Engineering

Job description

## Who we are Foundation models transformed text and images. Structured data - the largest and most consequential data format in the world - stayed untouched, until now. What LLMs did for language, we're doing for tables. We pioneered tabular foundation models: TabPFN v2 was a [Nature](https://www.nature.com/articles/s41586-024-08328-6) cover story, has passed 3.5M+ downloads and 7,500+ GitHub stars, and runs in production from [detecting lung disease with Oxford Cancer Analytics](https://www.oxcan.org/news/prior-labs-and-oxford-cancer-analytics-partner-to-advance-liquid-biopsy-and-clinical-decision-making-in-lung-disease) to [preventing train failures with Hitachi](https://siliconangle.com/2025/12/01/prior-labs-debuts-tabular-ai-foundation-model-scales-10-million-rows/). The hardest problems - millions of rows, real-time inference, entirely new modalities - are still open, and no one else is working on them at this level. We're a [small, highly selective team of 40+](https://priorlabs.ai/about) with backgrounds from Google, DeepMind, Meta, Apple, Amazon, Jane Street, and CERN, led by [Frank Hutter](https://www.linkedin.com/in/frank-hutter-9190b24b/), [Noah Hollmann](https://www.linkedin.com/in/noah-hollmann-668b9010b/), and [Sauraj Gambhir](https://www.linkedin.com/in/sauraj-g/), and advised by Bernhard Schölkopf and Turing Award winner Yann LeCun. In July 2026, less than 18 months after our €9M pre-seed, we [joined SAP](https://priorlabs.ai/blog-posts/priorlabs-sap) as an independent frontier AI lab - same team, mission, and open-weights models, now backed by more than €1 billion over four years. ## The role You will be our first dedicated engineering leader, reporting to the CTO with a direct line to both founders - no layers in between. Today, engineering at Prior Labs is a small, very senior team. We plan to grow it substantially over the next 18 months, and your job is to build and run that organization. We want to be honest about what this job is. It is a hands-on operator role: managing engineers, building the hiring machine, setting standards, running compliance, and working closely with our partners at SAP. If you light up at making an organization fast rather than at owning the biggest possible headcount, this is your role. **What you'll do** - Directly manage and grow the engineering team, including building out its management layer. - Build the hiring machine: run hiring operations across our hiring managers, design interview loops that hold up in the AI era, and keep a very high bar while the team grows. - Own engineering standards and velocity: how we review, test, and ship - and how the team gets real leverage from AI coding tools. - Own our security and compliance program - SOC 2, GDPR, ISO 27001 - right-sized, so the lab keeps its speed. - Own the engineering side of our collaboration with SAP. - Treat the deployment layer as a product surface: our models reach customers through a managed API, customer VPCs, and self-hosted open weights, and the engineering behind that needs customer empathy, not just platform craft. - Act as a sparring partner to the founders on org design and engineering direction - we're hiring someone who will argue with us. **What we're looking for** - You have directly led an engineering organization of 10+ people, including through managers or leads, and you can talk concretely about how you built it. - You have owned platform or infrastructure scope at scale: serving, APIs, availability, cloud and vendor budgets. - You have operated under SOC 2 / ISO-style audit regimes; having built or run the function yourself is a plus, not a requirement. - You have worked in both startups and large organizations - you can create structure from scratch and hold your own with a very large partner. **What sets you apart** - You scaled an engineering org through a real growth phase (25 to 60+ or similar), building the management layer along the way. - You have led engineering through an acquisition, working directly with the parent company. - You have led engineering in a research- or ML-heavy organization and know how research code and production code differ - and how to bridge them without slowing research down. - You have personally changed how your team works because of AI coding tools, and can show what it did to output. ## Life at Prior Labs You'll work alongside researchers and builders who hold themselves to a very high bar - in the quality of their work and in how they work with each other. We move fast and still take the time to do things right. Our teams are based in Berlin, Freiburg, and New York - when you're working on something as hard as TabPFN, being in the same room matters. But great people come from everywhere, and in exceptional cases we're open to remote, which usually means frequent travel to one of our offices. Wherever you're based, the whole company comes together regularly for offsites to build and celebrate together. ## Our Commitments The best products and teams are built by people with a wide range of perspectives and backgrounds. We welcome applications from all identities and walks of life - especially if you've ever felt discouraged by "not checking every box" - and provide equal opportunities regardless of gender, sexual orientation, origin, disability, or any other trait that makes you who you are. We care about how your data is handled - see our [Recruiting Data Privacy](https://priorlabs.ai/recruiting-data-privacy) page