Senior Software Engineer, Operator Tools

• Desktop application development for mission planning, real-time telemetry, and vehicle diagnostics (Qt, Electron, or similar native/hybrid desktop frameworks)
• Visualization and data presentation for complex, time-series, and spatial data from autonomous systems
• Communication interfaces between desktop tools and embedded systems (serial, UDP, custom protocols, MAVLink or similar)
• Ground support tooling: calibration workflows, pre-flight checks, log analysis, and fleet management interfaces
• Collaboration with the simulation infrastructure team to expose cloud batch results in accessible, actionable UI
• Web-based data analysis and visualization tools that connect to cloud databases. Think interactive flight data replay, post-mission analysis dashboards, and fleet-level trend reporting
• C++ and Python development across the stack; comfort moving between application logic and lower-level interfaces
• Contribution to the team’s overall software architecture and developer experience, particularly for tooling and internal platforms

You probably have:

• 5+ years of professional software development, with experience across desktop application development and web-based tools, ideally both
• Strong C++ and/or Python skills; experience structuring non-trivial desktop applications
• A track record of building UIs that are usable under real-world operational conditions, not just demos
• Ability to work across the stack: from application logic down to protocol parsing or up to data visualization
• Experience integrating applications with real hardware or real-time data sources
• High standards for software architecture, API design, and internal tooling quality

It’s a bonus if you have:

• Experience in aerospace, defense, robotics, or other safety-critical domains
• Familiarity with embedded software concepts: you don’t need to write firmware, but you should be able to read it, build it, run it, and understand its constraints
• Experience with cloud-based simulation or batch processing infrastructure
• Exposure to geospatial visualization, 3D rendering, or time-series data at scale
• Primary languages: C++ and Python
• Desktop frameworks: Qt and/or Electron (we’re pragmatic and flexible about tooling choices)
• Web UI: React or similar modern framework for cloud-connected data visualization and analysis tools; backends in Python
• Data: custom telemetry protocols, time-series logs, simulation output from cloud batch runners
• Version control and CI: Git, GitHub, cloud-based batch simulation and test runners
• Modern AI coding tools used as productivity accelerators, not as a substitute for engineering judgment