Software Engineer – Backend & Distributed Systems

About the role

We are hiring software engineers to build the backend and distributed systems that power an AI‑native physical science lab. The team creates reliable execution platforms for large simulation workloads, experiment orchestration, and instrument automation.

Key responsibilities

• Design and implement backend and distributed systems that execute scientific work reliably.
• Build scheduling and orchestration for long‑running workflows across compute clusters, instruments, and shared resources.
• Create clear APIs, data models, and service boundaries linking research software, lab information systems, and automation.
• Ensure execution is observable, recoverable, and provenance‑tracked through durable state and failure handling.
• Transform research prototypes and scientific workflows into maintainable production services.
• Diagnose performance bottlenecks and failures across code, infrastructure, data, and hardware integrations.
• Collaborate closely with scientists and engineers to improve experimental throughput, reliability, and reproducibility.

Required profile

• Strong software engineering fundamentals with a track record of building production backend or distributed systems.
• Experience with asynchronous or long‑running workloads such as batch jobs, workflow orchestration, data pipelines, or schedulers.
• Ability to reason about concurrency, idempotency, partial failures, consistency, and resource contention.
• Proficiency in designing maintainable APIs and data models for complex systems.
• Excellent debugging skills across services, infrastructure, dependencies, and data.
• Comfort turning ambiguous scientific needs into reliable, scalable software.

Required skills