Lead Software Engineer

Technology Innovation Institute (TII) is a publicly funded research institute, based in Abu Dhabi, United Arab Emirates. It is home to a diverse community of leading scientists, engineers, mathematicians, and researchers from across the globe, transforming problems and roadblocks into pioneering research and technology prototypes that help move society ahead. Role Overview • As an experienced Lead Engineer with expertise in flight control systems and companion compute platforms, your leading role will be in designing, implementing, and maintaining software solutions across NXP-based PX4 flight controllers and Nvidia-based and Qualcomm-based mission computers. You will optimize solutions for reliability, safety, and performance in complex UAV operations. • This position requires a deep understanding of real-time embedded systems, proficiency in PX4 autopilot software, and the ability to integrate high-performance applications on NVIDIA& Qualcomm IQ9 platforms. As a leader in our UAV development projects, you will play a key role in shaping our autonomy stack, ensuring scalability, safety, and secure communication across the system. • Lead engineer will take ownership in developing SW features and productization of the TII Secure Software Platform for large-scale defense UxV (Unmanned Vehicle) mission computer applications. Functional Activities Autonomy Software Development:  • Integrate robotics applications on NVIDIA & Qualcomm IQ9 platforms for perception, planning, and navigation.  • Develop and integrate ROS2-based nodes and middleware to support modular autonomy stacks.  • Optimize GPU-based AI/ML workloads for real-time inference, sensor fusion, and decision-making. System Integration and Middleware:  • Experience implementing secure application-level network protocols (NATS, ACL, DDS, etc.) between robotic platforms and Ground Control Station • applications, including message exchange, authentication, encryption, telemetry, command/control flows, and secure communication handling. • Develop tools and APIs for efficient data exchange across mission-critical components.  • Support multi-sensor integration (camera, LiDAR, GNSS, IMU) with ROS2 middleware.  • Has basic understanding on Flight Controller devices and PX4-based flight-control platforms, including real-time operation, MAVLink/UDP communication, telemetry, command/control flows, parameter management, sensor/peripheral interfaces, and integration with NVIDIA-based Mission Computer software. • Ability to work with Flight Controller hardware, FPGA, security, and systems teams to validate end-to-end integration across Mission Computer, Flight Controller, Ground Control Station, and unmanned vehicle platforms. Security and Reliability:  • Design and enforce cybersecurity measures for UAV autonomy software (secure boot, encrypted comms, sandboxing).  • Implement identity management and access control for mission software deployments.  • Conduct threat modeling, vulnerability assessments, and apply secure coding practices.  • Ensure compliance with aerospace cybersecurity frameworks (ISO 27001, DO-326A).  Automation and DevOps:   • Build CI/CD pipelines for deployment of ROS2 and AI workloads on NVIDIA Jetson and Qualcomm IQ9. • Use containerization (Docker) and orchestration tools for reproducible autonomous flight stacks.  • Apply understanding of MATLAB and related engineering tools for automation, test scripting, data analysis, model-based workflows, validation support, and manufacturing procedure automation. Engineering Process Optimization:  • Implement telemetry, logging, and diagnostics for real-time system monitoring.  • Continuously optimize software for GPU utilization, latency reduction, and energy efficiency.  • Define and enforce best practices in software development lifecycle (SDLC) for autonomy stack.  • Standardize coding guidelines, documentation, and review processes to ensure maintainability and quality.  • Define KPIs (e.g., deployment cycle time, test coverage, system uptime, security incidents) to track engineering efficiency.  • Encourage reuse of components and frameworks across projects to reduce duplication.  • Organize regular code reviews, technical retrospectives, and knowledge-sharing sessions.  • Sprint planning, backlog grooming, and daily stand-ups.  • Automated testing, HITL/SITL, code review, and release management.  • Metrics tracking, velocity, and continuous improvement of the engineering process.  Industry / Domain Defense Autonomous Systems / Secure Mission Computing / Unmanned Vehicles (UxV) Necessary Knowledge And Experience • 10+ years of experience in robotics, autonomous systems, or safety-critical UxV platform development, preferably in defense or aerospace environments. • Proficiency in real-time embedded systems and Python for automation, AI/ML workflows, testing, and data pipelines. • Strong experience with ROS2, XRCE-DDS, MAVLink, and modular autonomy stack architecture on NVIDIA Jetson and Qualcomm-based mission computer platforms. • Hands-on experience with Qualcomm SoC platform bring-up, including BSP integration, Linux/Yocto environments, boot chain validation, peripheral enablement, driver integration, and platform debugging. • Understanding of Qualcomm security features, including secure boot, hardware root of trust, TEE, key provisioning, encrypted storage, anti-rollback, secure debug control, and lifecycle-state enforcement. • Experience with production security workflows, including fuse burning, root-of-trust provisioning, device identity, factory flashing, secure provisioning, and manufacturing test procedures. • Hands-on experience with GPU, DSP, NPU, or AI accelerator-based workloads for sensor fusion, real-time inference, and SWaP-constrained AI/ML deployment. • Experience implementing embedded cybersecurity measures, including encrypted communications, sandboxing, access control, threat modeling, secure OTA, and secure coding practices. • Familiarity with ISO 27001, DO-326A, DevOps/CI/CD, Git, Docker, Kubernetes, automated testing, and cross-functional integration. • Strong English communication skills and ability to work with software, hardware, security, manufacturing, QA, and systems teams under pressure. Education And Certification Requirements • Experience in UAV or aerospace autonomy projects.  • Contributions to the ROS2 or NVIDIA Jetson open-source community.  • Knowledge of ML, SLAM, or multi-agent coordination.  • Familiarity with standards (ISO 27001, DO-178C, DO-326A, IEC 61508).  • Proven track record of bringing autonomous systems from concept to product, including field deployment and user adoption.  At TII, we help society to overcome its biggest hurdles through a rigorous approach to scientific discovery and inquiry, u

Necessary Knowledge And Experience: 10+ years of experience in robotics, autonomous systems, or safety-critical UxV platform development, preferably in defense or aerospace environments. Proficiency in real-time embedded systems and Python for automation, AI/ML workflows, testing, and data pipelines. Strong experience with ROS2, XRCE-DDS, MAVLink, and modular autonomy stack architecture on NVIDIA Jetson and Qualcomm-based mission computer platforms. Hands-on experience with Qualcomm SoC platform bring-up, including BSP integration, Linux/Yocto environments, boot chain validation, peripheral enablement, driver integration, and platform debugging. Understanding of Qualcomm security features, including secure boot, hardware root of trust, TEE, key provisioning, encrypted storage, anti-rollback, secure debug control, and lifecycle-state enforcement. Experience with production security workflows, including fuse burning, root-of-trust provisioning, device identity, factory flashing, secure provisioning, and manufacturing test procedures. Hands-on experience with GPU, DSP, NPU, or AI accelerator-based workloads for sensor fusion, real-time inference, and SWaP-constrained AI/ML deployment. Experience implementing embedded cybersecurity measures, including encrypted communications, sandboxing, access control, threat modeling, secure OTA, and secure coding practices. Familiarity with ISO 27001, DO-326A, DevOps/CI/CD, Git, Docker, Kubernetes, automated testing, and cross-functional integration. Strong English communication skills and ability to work with software, hardware, security, manufacturing, QA, and systems teams under pressure. Education And Certification Requirements: Experience in UAV or aerospace autonomy projects. Contributions to the ROS2 or NVIDIA Jetson open-source community. Knowledge of ML, SLAM, or multi-agent coordination. Familiarity with standards (ISO 27001, DO-178C, DO-326A, IEC 61508). Proven track record of bringing autonomous systems from concept to product, including field deployment and user adoption.

Autonomy Software Development: Integrate robotics applications on NVIDIA & Qualcomm IQ9 platforms for perception, planning, and navigation. Develop and integrate ROS2-based nodes and middleware to support modular autonomy stacks. Optimize GPU-based AI/ML workloads for real-time inference, sensor fusion, and decision-making. System Integration and Middleware: Experience implementing secure application-level network protocols (NATS, ACL, DDS, etc.) between robotic platforms and Ground Control Station applications, including message exchange, authentication, encryption, telemetry, command/control flows, and secure communication handling. Develop tools and APIs for efficient data exchange across mission-critical components. Support multi-sensor integration (camera, LiDAR, GNSS, IMU) with ROS2 middleware. Has basic understanding on Flight Controller devices and PX4-based flight-control platforms, including real-time operation, MAVLink/UDP communication, telemetry, command/control flows, parameter management, sensor/peripheral interfaces, and integration with NVIDIA-based Mission Computer software. Ability to work with Flight Controller hardware, FPGA, security, and systems teams to validate end-to-end integration across Mission Computer, Flight Controller, Ground Control Station, and unmanned vehicle platforms. Design and enforce cybersecurity measures for UAV autonomy software (secure boot, encrypted comms, sandboxing). Implement identity management and access control for mission software deployments. Conduct threat modeling, vulnerability assessments, and apply secure coding practices. Ensure compliance with aerospace cybersecurity frameworks (ISO 27001, DO-326A). Build CI/CD pipelines for deployment of ROS2 and AI workloads on NVIDIA Jetson and Qualcomm IQ9. Use containerization (Docker) and orchestration tools for reproducible autonomous flight stacks. Apply understanding of MATLAB and related engineering tools for automation, test scripting, data analysis, model-based workflows, validation support, and manufacturing procedure automation. Engineering Process Optimization: Implement telemetry, logging, and diagnostics for real-time system monitoring. Continuously optimize software for GPU utilization, latency reduction, and energy efficiency. Define and enforce best practices in software development lifecycle (SDLC) for autonomy stack. Standardize coding guidelines, documentation, and review processes to ensure maintainability and quality. Define KPIs (e.g., deployment cycle time, test coverage, system uptime, security incidents) to track engineering efficiency. Encourage reuse of components and frameworks across projects to reduce duplication. Organize regular code reviews, technical retrospectives, and knowledge-sharing sessions. Sprint planning, backlog grooming, and daily stand-ups. Automated testing, HITL/SITL, code review, and release management. Metrics tracking, velocity, and continuous improvement of the engineering process.