Software Engineer (Backend)

Join Normal, a frontier AI company, as an Infrastructure Software Engineer. In this application engineering role, you will build the production systems behind Normal's AI products, focusing on infrastructure-shaped software. You will design internal backend services and APIs, improve operational maturity, and collaborate closely with product, AI, research, and platform engineers. This is a highly cross-functional role that requires strong software engineering fundamentals, experience with orchestration systems, and a comfort with persistence systems.

• Construire et maintenir l'infrastructure logicielle de production pour les produits d'IA de Normal, en particulier les systèmes d'orchestration, d'exécution et d'exécution.
• Concevoir des services backend internes et des API utilisés par les ingénieurs produits, les ingénieurs IA, les services d'exécution et d'autres systèmes internes.
• Améliorer la maturité opérationnelle des systèmes en évolution rapide grâce à une meilleure gestion de l'état, à la gestion des pannes, aux métriques, à la traçabilité et aux outils de débogage.
• This is a highly cross-functional role for someone who enjoys ambiguity, cares about clean abstractions, and wants to help shape how a frontier AI company builds and operates production systems. Strong engineering judgment and ownership matter more than rigid specialization
• Strong software engineering fundamentals, including backend programming, APIs, data modeling, concurrency, debugging, and testing
• Experience building orchestration systems, job schedulers, workflow engines, sandboxes, developer platforms, or distributed execution systems
• Practical experience with Docker and Kubernetes, including debugging containerized workloads, deployments, networking, resource limits, and lifecycle issues
• Comfort working with persistence systems such as Postgres, Redis/Valkey, object storage, or similar production data stores
• Experience designing internal APIs and developer-facing abstractions that other engineers can use confidently
• Clear communication and good technical judgment across product, AI, and infrastructure boundaries
• Experience building or operating production services where reliability, observability, and maintainability matter
• Strong systems thinking: you can reason about state machines, failure modes, retries, queues, leases, scheduling, and long-running workflows
• 4+ years of experience in infrastructure software, backend infrastructure, production infrastructure, platform engineering, distributed systems, or related areas
• Pragmatism in fast-moving environments: you know when to improve an abstraction, when to delete one, and when to ship the simple version
• Ownership mindset: you care whether the systems you build work in production and are usable by other engineers
• Deep Kubernetes experience, such as controllers/operators, networking, storage, scheduling, autoscaling, or resource isolation
• Background in production infrastructure, reliability engineering, or infrastructure software at meaningful scale
• Experience in high-growth startups or engineering teams where ownership boundaries are still being defined
• Experience with AI agent infrastructure, ML infrastructure, model orchestration, or LLM-based product systems
• Experience with Chips, EDA or Device Verification