Principal Software Engineer

• Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability.
• Own core runtime foundations: distributed control, state management, fault handling, and reliability.
• Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes.
• Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints).
• Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes.
• Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress.

What you'll do

• Act as the technical lead for large parts of the scanner platform: system architecture, codebase structure, and long-term maintainability.
• Own core runtime foundations: distributed control, state management, fault handling, and reliability.
• Drive engineering rigor: testability, code quality, review standards, performance regression prevention, and release processes.
• Build robust observability: logs, metrics, traces, and replayable diagnostics (with privacy constraints).
• Collaborate with hardware and recon/ML teams to define interfaces, data contracts, timing/synchronization, and failure modes.
• Lead complex refactors (e.g., message passing / RPC boundaries, modularization, concurrency model) without halting forward progress.

What we're looking for

• Deep software architecture experience for real-world systems: robotics, instrumentation, medical devices, or other complex distributed products.
• Strong Python and concurrency background (asyncio, multiprocessing, profiling, performance engineering).
• Track record of shipping systems that are observable, debuggable, and resilient.
• Strong technical leadership: clarity, pragmatic trade-offs, and mentoring.

Useful experience

• Building but rock-solid systems: clear interfaces (gRPC/protobuf or equivalent), strong state modeling, and failure handling.
• High-leverage engineering habits on a lean team: good tests, CI, reproducible dev environments, and fast code review.
• Practical performance + concurrency work in Python (asyncio, profiling, multiprocessing) and comfort debugging distributed behavior.
• Security-minded device software: safe defaults, encrypted data paths, and disciplined handling of PII/PHI.
• Operational thinking: remote updates/management, excellent logging, and diagnostics that make real hardware debuggable.