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The Principal Engineer, Hardware will lead design, integration, and manufacturing of autonomous vehicle systems, ensuring reliability and compliance with safety standards across mechanical and electrical disciplines.

The Chief of Staff will drive project execution, manage leadership schedules, provide strategic insights, and enhance operational efficiency while facilitating team collaboration.

Lead the autonomy organization at AeroVect, managing the entire autonomy team and technical roadmap, ensuring successful execution across various modules.

Lead AeroVect's hardware organization, managing hardware teams across various engineering disciplines to deliver autonomous vehicle platforms and ensure production readiness, reliability, and safety compliance.

The Staff Software Engineer, Infrastructure will design and scale infrastructure for autonomous systems, mentor engineers, and ensure reliability and performance in software delivery through robust CI/CD pipelines and cloud solutions.

The Principal Engineer for Autonomy leads technical direction in Perception, Prediction, and Planning within the autonomy organization, ensuring robust integration and execution on real vehicles.

Field-based integration engineer for autonomous ground handling platforms. Validate sensors and hardware, run supervised autonomy tests, debug software in the field, maintain fleet software, collect and document test data, and train/test operators to improve deployment readiness and minimize downtime.

Operate and test autonomous tractors on-site, report and debug abnormal behavior, analyze logs and system data, and identify process and tooling optimizations while collaborating with engineers.

The Senior Technical Program Manager will oversee the ATL program, ensuring cross-functional execution and managing program schedules, risks, and stakeholder meetings, while maintaining program governance and tracking health ahead of milestones.

Own and productionize core localization systems (state estimation, mapping, calibration). Build monitoring, diagnostics, validation, and deployment tooling. Integrate sensors, tune performance, run regression testing, and iterate using data from real autonomous airport operations to enable driverless capability.