Principal Software Engineer
Listed by employer · Checked
Older posting · still listed ·
- Work arrangement
- onsite
- Employment
- FullTime
- Stated compensation
- USD 268,000–279,000 1 YEAR
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Requirements
1 with evidence8 unclear or unstated- Remote policy
- onsite
“Provider workplace type: onsite”
From employer posting metadata - Employment type
- FullTime
- Compensation
- USD 268,000–279,000 1 YEAR
8 fields not stated in this posting
- Employer sponsorship
- Not specified
- Geographic scope
- Not specified
- Degree requirement
- Not specified
- Security clearance
- Not mentioned
- Timezone / hours
- Not specified
- Citizenship requirement
- Not mentioned
- Minimum experience (years)
- Not specified
- Work authorization
- Not specified
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Original job description
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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.
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