Journeyman Software Engineer

Description

In this role, you will be responsible for independently managing the porting of autonomy software between baselines while simultaneously designing and maintaining the sophisticated simulation and hardware-in-the-loop (HIL) environments required for validation. You will bridge the gap between core software development and rigorous system-level testing, ensuring that autonomous platforms are reliable, high-performing, and mission-ready.

• Autonomy Software Development Porting and Integration:
  Independently lead the migration and adaptation of autonomy software components across different software baselines, ensuring functional parity and performance optimization.
• Test Environment Architecture:
  Design, implement, and maintain advanced test environments, including Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) simulations, to validate complex autonomy algorithms.
• Automated Testing and Frameworks:
  Develop reusable automated test scripts and frameworks to replace manual verification processes, increasing test coverage and reducing feedback cycles.
• System Integration:
  Collaborate with cross-functional teams to integrate autonomy software with vehicle management systems, sensors (LiDAR, Vision), and mission payloads.
• Dev Ops and CI/CD:
  Establish and optimize CI/CD pipelines to automate regression testing, build processes, and software deployments for autonomous systems.
• Validation and Reporting:
  Execute comprehensive test plans, analyze simulation data to identify edge-case failures, and provide detailed technical reports to senior leadership.

• Active DoD Secret Security Clearance.
• Bachelor's degree in Computer Science, Software Engineering, Aerospace Engineering, or a related field.
• Five (5) to ten (10) years of professional software engineering experience, specifically within autonomous systems, robotics, or complex embedded software.

• Technical Proficiency:
  Strong proficiency in C++ and Python within Linux-based development environments.
• Tooling and Version Control:
  Expert-level knowledge of Git, CMake, and debugging tools.
• Domain Expertise:
  Demonstrated experience building or maintaining simulation environments.

• Real-Time Systems:
  Experience with Real-Time Operating Systems (RTOS) or safety-critical software standards (e.g., DO-178C).
• Advanced Simulation:
  Familiarity with Hardware-in-the-Loop (HIL) testbench design and data acquisition systems.
• Modern Dev Ops:
  Knowledge of containerization (Docker/Kubernetes) and Infrastructure for managing test environments.
• AI/ML Testing:
  Experience validating machine learning models or sensor fusion pipelines in autonomous contexts.

• On some occasions, the employee may be required to drive to offices or buildings near the work site. In rare occasions, travel may be required.