We're looking for a Full-Stack Engineer with strong backend and DevOps background to help build and evolve internal tools that power AI research and evaluation. This role sits at the intersection of backend architecture, infrastructure automation, and developer experience - with the larger goal of improving how we measure and ensure the quality and safety of AI systems.You'll collaborate closely with machine-learning researchers, data scientists, PMs, and engineers, translating complex research workflows into robust, scalable systems. While your primary focus will be on backend services, data models, and infrastructure, you'll also occasionally contribute to frontend development to help shape cohesive, user-friendly interfaces that bring research workflows to life.What You'll Work On Designing and implementing backend APIs and data models using modern web frameworks (e.g. Laravel, Ruby on Rails, Node.js / Adonis, or Python / FastAPI) Managing MongoDB schemas and performing safe data migrations for live research datasets Building and maintaining Dockerized applications and CI/CD pipelines in Kubernetes / Argo CD environments Maintaining and versioning APIs and SDKs following Semantic Versioning (SemVer), and communicating updates clearly to internal users Working directly with internal customers to understand workflows, gather requirements, and translate them into actionable engineering tasks Automating developer processes and improving tooling and developer experience across the platform Occasionally contributing to frontend development (React or similar frameworks) to integrate new backend features or streamline researcher-facing workflows