Create Alert

Lead Software Engineer

Apply now »

Date: 6 Aug 2026

Location: AE

Company: Technology Innovation Institute

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.