Senior Engineer, Software Autonomy (R3144)

As a Senior Engineer, Software Autonomy at Shield AI, you will design and develop software components for the VBAT autopilot, implement effective testing frameworks, and improve our build processes and tooling. You'll also lead the optimization of our C++ architecture and collaborate with teams to define interfaces between system components, ensuring a seamless integration of services.

To qualify for the Senior Engineer, Software Autonomy role at Shield AI, candidates typically need at least 5 years of relevant experience accompanied by a Bachelor's degree, or advanced degrees like a Master's or PhD with lesser experience. A strong background in C++ 11 or newer is essential, along with a proven ability to deliver complex software products in a fast-paced environment.

Excelling in the Senior Engineer, Software Autonomy position at Shield AI involves demonstrating excellent problem-solving and analytical skills while maintaining a user-centric approach in software solutions. Being a trustworthy teammate who meets high standards and maintains good team dynamics is equally important for success in this collaborative environment.

While not mandatory, familiarity with robotics or control systems, particularly those related to aerial systems, is preferred for the Senior Engineer, Software Autonomy role at Shield AI. This knowledge can significantly enhance your ability to contribute to the team's goals and tackle specific technical challenges efficiently.

The salary for the Senior Engineer, Software Autonomy position at Shield AI ranges from $158,400 to $237,600 per year, depending on various factors such as skill set and experience. The total compensation package includes benefits, bonuses, and equity for eligible positions, providing a comprehensive employment offer.

In my previous roles, I worked extensively with C++ in developing complex software for autonomous systems. I successfully navigated through various development cycles, overcoming technical obstacles to deliver software that was both robust and user-friendly. C++ enabled me to optimize performance and handle real-time data processing, which is critical for autonomous applications.

My approach to software testing for autopilot systems involves implementing thorough test frameworks that encompass unit tests and integration tests. I prioritize early detection of issues by simulating real-world scenarios. Continuous integration practices also allow for rapid iterations and improvements based on testing feedback.

To improve CI pipelines, I focus on automating build and test processes to minimize manual interventions. This includes using containerized environments to ensure consistency across all development stages and integrating tools that provide instant feedback on code quality, which enhances collaboration within the development team.

In one challenging project, I led the development of a software component for an autonomous drone. We faced tight deadlines and technical limitations, but through effective team collaboration and agile methodologies, we redefined our design process, allowing us to identify and address issues early on, ultimately succeeding in delivering a high-quality product on time.

To ensure compliance with software design standards, I implement regular code reviews where team members can audit each other's work. I also advocate for adherence to established coding standards and guidelines during all phases of development, as well as employ static analysis tools to catch potential issues early in the process.

I have hands-on experience using Docker and Kubernetes to containerize applications, which enhances their portability and scalability. Implementing containerization allowed our team to create consistent testing environments and streamline deployment processes, significantly recognizing improvements in our software development lifecycle.

When faced with tight deadlines, I prioritize effective communication and collaboration with my team to ensure alignment on goals. I assess the critical path of tasks and focus on delivering core functionalities first, allowing for a phased approach where additional features can be added as time permits.

One of the most critical qualities for a Senior Engineer at Shield AI is being a great collaborator. This role requires working closely with cross-functional teams, so the ability to communicate ideas and feedback openly while also being approachable and supportive is vital for achieving the best outcomes in projects.

I view user feedback as an invaluable asset in product development. I champion creating channels where users can share their experiences, using that information to iterate and enhance product features based on actual needs rather than assumptions. This leads to higher user satisfaction and better product functionality.

I find the advancements in machine learning and artificial intelligence for autonomy particularly exciting. These technologies allow for improved decision-making and adaptability in real-time scenarios, significantly enhancing the operational capabilities of autonomous systems and ensuring they perform reliably in complex environments.