Software Engineer

About the role

Radical AI is building a self‑driving lab platform that fuses AI with autonomous robotics to accelerate scientific discovery. As a generalist software engineer you will contribute to the core platform that controls, monitors, and orchestrates physical experiments across cloud and on‑prem environments.

Key responsibilities

• Design and implement backend services for experiment definition, path‑planning, and durable task execution.
• Develop data infrastructure: database schemas, migrations, ETL pipelines, and object‑storage designs.
• Build internal developer platforms, SDKs, and shared services.
• Implement observability solutions using structured logs, metrics, tracing (OpenTelemetry, Prometheus/Grafana) and production debugging tools.
• Manage hybrid cloud/on‑prem infrastructure with containerization, orchestration, and IaC.
• Create agent tooling for API integrations, code execution, literature retrieval, and workflow automation.
• Engineer scientific workflow orchestration, including Bayesian optimization loops, experiment scheduling, retries, and idempotency.

Required profile

• 5‑6+ years of production software engineering experience.
• Strong systems thinking and production instincts for high‑reliability, real‑world physical systems.
• Experience navigating hybrid cloud/on‑prem constraints and distributed‑system failure modes.

Required skills

• Proficiency in Go and/or Python (additional experience with TypeScript or Rust is a plus).
• Deep understanding of distributed systems concepts: timeouts, retries, idempotency, dead‑letter queues, safe rollback.
• Concurrent and asynchronous programming expertise.
• Solid networking fundamentals.
• Containerization and cloud deployment experience (Kubernetes, AWS).
• Linux system debugging.
• Observability tooling: OpenTelemetry, Prometheus, Grafana.
• Infrastructure‑as‑code and orchestration knowledge.