Lead System Architect - Autonomous Vehicle

SteerAI is an autonomous mobility technology company powered by VentureOne, the commercialization arm of the Advanced Technology Research Council. SteerAI’s advanced AI-powered autonomy stack, developed by the Technology Innovation Institute, empowers the logistics and defense industries by turning industrial vehicles into autonomous powerhouses that can handle complex off-road missions, transforming operations and protecting organizations' most important assets: Their workforce. Role Overview We are seeking a highly skilled and experienced Lead System Architect to join our cutting-edge autonomous robotics team. The ideal candidate will lead the design, integration, and optimization of robotic systems, particularly for autonomous vehicles and ground robots. You will collaborate with cross-functional teams, ensuring scalable, reliable, and high-performance robotic solutions that meet technical, safety, and regulatory standards. Responsibilities • System Architecture Design: Lead the development of scalable and robust architectures for autonomous robotic systems, ensuring they meet performance goals and align with system requirements. • Solution Design & Integration: Work with hardware, software, and AI teams to integrate sensors, computing platforms, communication modules, and control systems into cohesive robotic solutions. • System Requirements Specification (SRS): Define and maintain system requirements, ensuring they are clear, traceable, and verifiable. Manage requirements lifecycle from definition to validation. • Model-Based Systems Engineering (MBSE): Utilize SysML to model and design systems, ensuring effective integration and clear representation of system components. • Risk Management & Safety Compliance: Identify and mitigate risks in the system design, ensuring compliance with functional safety standards (e.g., ISO 26262) and regulatory requirements for autonomous systems. • Prototyping & Validation: Guide prototype development, testing, and validation of systems against defined requirements and performance indicators. • Cross-Functional Collaboration: Collaborate with multidisciplinary teams (hardware, software, AI, and product) to ensure seamless integration and alignment. • Documentation & Reporting: Maintain comprehensive technical documentation, including system diagrams, design specifications, and progress reports for stakeholders. • Mentorship & Leadership: Lead architectural reviews, mentor junior engineers, and align team efforts with project milestones. Requirements • Education: Bachelor’s or Master’s degree in Systems Engineering, Robotics, Mechatronics, Electrical Engineering, Computer Science, or related field. • Experience: 8+ years in system architecture or systems engineering, with experience in autonomous vehicle systems or ground robotics. • Technical Expertise: Strong understanding of systems engineering principles, including the V-model, SysML, MBSE, sensor fusion, and autonomous vehicle technologies. • Software & Tools: Proficiency in tools such as MATLAB, Simulink, ROS, and architecture modeling tools (e.g., Enterprise Architect, MagicDraw). • Communication Skills: Strong verbal and written communication skills, able to present complex technical concepts to both technical and non-technical audiences. • Problem-Solving Skills: Excellent analytical and problem-solving abilities, particularly in integrating complex systems and addressing design challenges. Preferred Skills: • Autonomous Systems: Experience with autonomous vehicles, unmanned ground vehicles (UGVs), or field robotics. • Safety Standards: Familiarity with functional safety standards (e.g., ISO 26262, ISO 21448). • Emerging Technologies: Knowledge of AI, machine learning, edge computing, and cloud computing in autonomous systems. • Simulation & Testing: Experience with simulation tools (e.g., MATLAB, Simulink) and real-world testing of robotic systems. • Agile Development: Familiarity with Agile development methodologies. Soft Skills: • Leadership: Strong leadership abilities to mentor and guide cross-functional teams. • Collaboration: Excellent interpersonal skills, able to work effectively in fast-paced, startup environments. • Adaptability: Ability to tackle challenges with a proactive and adaptable approach What we offer We offer a competitive salary, a comprehensive benefits package, and the opportunity to work alongside some of the brightest minds in the Autonomous Robotics industry. Our work culture is collaborative and inclusive, with a strong focus on innovation and personal growth. If you're passionate about advancing the frontiers of Autonomous Robotics and eager to leave a lasting mark in this domain, seize the opportunity and apply today to join us in sculpting the future of this dynamic field! Show more Show less

Education: Bachelor’s or Master’s degree in Systems Engineering, Robotics, Mechatronics, Electrical Engineering, Computer Science, or related field. Experience: 8+ years in system architecture or systems engineering, with experience in autonomous vehicle systems or ground robotics. Technical Expertise: Strong understanding of systems engineering principles, including the V-model, SysML, MBSE, sensor fusion, and autonomous vehicle technologies. Software & Tools: Proficiency in tools such as MATLAB, Simulink, ROS, and architecture modeling tools (e.g., Enterprise Architect, MagicDraw). Communication Skills: Strong verbal and written communication skills, able to present complex technical concepts to both technical and non-technical audiences. Problem-Solving Skills: Excellent analytical and problem-solving abilities, particularly in integrating complex systems and addressing design challenges.

System Architecture Design: Lead the development of scalable and robust architectures for autonomous robotic systems, ensuring they meet performance goals and align with system requirements. Solution Design & Integration: Work with hardware, software, and AI teams to integrate sensors, computing platforms, communication modules, and control systems into cohesive robotic solutions. System Requirements Specification (SRS): Define and maintain system requirements, ensuring they are clear, traceable, and verifiable. Manage requirements lifecycle from definition to validation. Model-Based Systems Engineering (MBSE): Utilize SysML to model and design systems, ensuring effective integration and clear representation of system components. Risk Management & Safety Compliance: Identify and mitigate risks in the system design, ensuring compliance with functional safety standards (e.g., ISO 26262) and regulatory requirements for autonomous systems. Prototyping & Validation: Guide prototype development, testing, and validation of systems against defined requirements and performance indicators. Cross-Functional Collaboration: Collaborate with multidisciplinary teams (hardware, software, AI, and product) to ensure seamless integration and alignment. Documentation & Reporting: Maintain comprehensive technical documentation, including system diagrams, design specifications, and progress reports for stakeholders. Mentorship & Leadership: Lead architectural reviews, mentor junior engineers, and align team efforts with project milestones.