About the Role
As Head of Engineering, you will own the technical architecture, define engineering culture, hire and grow an engineering team, and shape how products are built and shipped. You will work closely with the Head of Science and Head of Research in a collaborative, fast-moving environment.
Responsibilities
- Own the technical roadmap, making architectural decisions that balance shipping speed with long-term scalability
- Drive the evolution of our cloud-based infrastructure
- Anticipate scaling and reliability challenges before they become expensive, staying ahead of the product to validate approaches and surface unknowns early
- Establish engineering practices and standards that will scale as the team grows from a handful of engineers to a full organization
- Champion AI-tool fluency across the team, using tools like Claude Code as force multipliers
- This is a building role, not a meetings role
- Make key technical decisions across backend services, data infrastructure, and developer tooling
- Drive measurable improvements in system performance, reliability, and operational cost
- Build a robust infrastructure that will scale, as we serve the needs of the global scientific community
- Be a true partner to the Head of Research and Head of Science — this is not a hand-off relationship, but tight collaborative loops
- Work in close alignment with product to translate user needs and requirements into engineering priorities
- Translate complex technical tradeoffs into clear, actionable guidance for technical and non-technical stakeholders alike
- Recruit, hire, and mentor a world-class engineering team across backend, frontend, infrastructure, and security
- Build a culture where shipping fast (excellence), learning continuously (curiosity), and being good humans (kindness) can coexist
- Foster an environment of intellectual humility, open source contribution, and AI-native development practices
Requirements
- Significant experience building and leading engineering teams at early-stage or high-growth companies
- Genuine fluency with AI coding tools: you already use them daily, to solve real problems, not just experimentally
- Deep hands-on expertise with cloud-native architectures
- Some experience with Model Context Protocol (MCP), agentic frameworks, or AI-tool integration patterns
- A track record of scaling and shipping production systems under real constraints, not just designing them, but delivering them
- Ability to operate with high autonomy in a fast-moving, resource-constrained environment
Nice to Have
- Experience with our stack or adjacent: Node.js/TypeScript, AWS Lambda/CDK/Step Functions, PostgreSQL, Cloudflare
- Experience scaling teams through key growth inflection points (e.g., 5 → 20 engineers)
- Familiarity with ML infrastructure, vector search, or document processing pipelines (added bonus for experience in research/academia)
- Familiarity with auth systems (e.g. OAuth) and observability tooling
