VP of Engineering, Full Stack (CTO Track)
- Compensation
- Not disclosed
- Location
- London, United Kingdom
- Work setup
- Hybrid
- Seniority
- C level
- Employment
- Full time
- Experience
- 10+ years
- Category
- Fullstack
- Posted
Skills
Nice to have
- Familiarity with safety and quality standards such as SOC 2, ISO 27001 or FedRAMP
- Experience building developer tools, IDEs, code editors (e.g. Monaco, VS Code extensions) or code analysis tooling
- Experience serving custom or fine-tuned models (vLLM, TensorRT-LLM, Triton or similar) and GPU infrastructure
- Rust or C/C++ experience
- Experience selling to and deploying in regulated or security-conscious enterprises
Full description
About the company
We're a frontier AI lab building our own foundation model for safety-critical embedded control software. Think motor controllers, battery management, power electronics and vehicle systems, where a bug is a physical failure, not a 500 error.
Our platform puts that model to work. Its user-facing product is the environment where control engineers specify, generate, review, test and trace embedded software with AI assistance.
Our foundation model is available now. The job is to integrate it into the product and turn it into something engineers trust, on an architecture that takes each new model release without a rewrite.
The role
You'll be the most senior engineer on the product and the person who decides how it's built. This is a hands-on role: you'll write a large share of the code in year one.
As the product and team grow, you'll grow into technical leadership of the platform, setting architecture, engineering standards and hiring. For the right person, this is a clear path to CTO.
You'll work directly with the founding team and the model research team. The bridge between a frontier model and a product that safety-critical engineers rely on runs through you.
Reports to: Founders
What you'll do
- Architecture: Own the architecture across frontend, backend, data and infrastructure, and make the build-vs-buy calls.
- Product delivery: Ship features fast, working closely with product and early users who are control and embedded engineers.
- Model integration: Design the integration layer (inference serving, prompt and context management, tool use, streaming, evaluation hooks and fallbacks) so we integrate our model now and adopt future releases without a rewrite.
- Trust workflows: Build what engineers need to trust AI-generated code: traceability from requirements to code, diffing and review, test execution and audit trails.
- Engineering foundations: Set up CI/CD, observability, security, access control and cost control for GPU-backed workloads.
- Enterprise readiness: Prepare the product for enterprise customers in regulated industries: SSO, data isolation, on-prem or private-cloud deployment.
- Team: Hire, mentor and lead the first engineers, and define how the team works.
What you bring
- 10+ years building and shipping production software, with real depth on both frontend and backend
- Strong TypeScript and React (or equivalent modern frontend), plus at least one backend language such as Python, Go or TypeScript/Node