Principal AI Engineer

ABOUT THE ROLE We are seeking a Principal AI Engineer to provide technical leadership in the design, development, integration, verification, and deployment of advanced AI and computer vision solutions for edge and mission-critical platforms. The role will serve as a senior technical authority across AI/ML, computer vision, video analytics, embedded software, and system architecture, working closely with AI, embedded, systems, hardware, test, product, and programme teams. The Principal AI Engineer will be responsible for taking complex AI systems from concept and architecture through development, integration, verification, certification, and field deployment. The role requires strong hands-on expertise in Python and C++, deep learning, computer vision, video analytics, and edge AI, combined with the ability to lead multi-disciplinary engineering teams without direct authority. The successful candidate will operate at a high level of technical autonomy, make architecture and technology decisions under real-world constraints such as latency, power, memory, compute capacity, reliability, and certifiability, and establish engineering practices that support the development of robust, production-ready and safety-relevant AI systems. RESPONSIBILITIES • Define and develop software requirements based on system-level requirements and translate them into robust software architectures and designs. • Lead the architecture, design, development, integration, verification, and deployment of AI and computer vision software. • Design, develop, and maintain high-performance video analytics and AI software using Python and C++, particularly for edge and embedded platforms. • Lead the development and implementation of object detection, tracking, recognition, classification, and other computer vision algorithms. • Develop novel AI/ML algorithms and make principled architecture selections based on application requirements and constraints. • Design scalable software architectures, system decomposition, interfaces, and integration strategies across multi-team engineering environments. • Lead technical resolution of complex software, AI, computer vision, and embedded-system issues across PC and edge devices. • Perform system-level profiling and optimization across CPU, GPU, memory bandwidth, I/O, and other system resources to resolve performance bottlenecks. • Lead software integration activities and ensure effective integration across AI, embedded, hardware, systems, and test components. • Define and enforce software development standards, coding practices, code review processes, testing methodologies, and quality gates. • Lead technical teams and projects, providing mentorship and technical direction while influencing teams without direct authority. • Collaborate with multidisciplinary teams to identify and solve complex problems using advanced AI, computer vision, and video analytics techniques. • Develop communication protocols, software interfaces, and system integrations required for AI-enabled platforms. • Plan and execute software verification activities including testing, analysis, inspections, and technical reviews. • Ensure software development follows the V-model and applicable engineering, quality, safety, and configuration-management processes. • Contribute to and lead major programme milestones and technical reviews, including SDR, PDR, CDR, TRR, and related design and readiness reviews. • Support the complete product lifecycle from concept and architecture through production, certification, deployment, and field support. • Ensure compliance with applicable company processes, quality-management requirements, statutory requirements, safety requirements, and engineering standards. • Provide technical support during system testing, integration activities, and field deployments when required. • Stay current with emerging AI/ML, computer vision, edge computing, and vide • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Computer Engineering, or a related technical discipline. • 12+ years of professional experience in software engineering, AI/ML engineering, computer vision, or a closely related field. • At least 4+ years of experience in a Principal Engineer, Lead Engineer, Software Architect, Technical Lead, or equivalent technical leadership role. • Strong hands-on programming experience in Python and C/C++. • Strong understanding of data science, machine learning, deep learning, and computer vision. • Extensive experience developing and deploying computer vision and video analytics solutions. • Strong understanding of deep learning architectures, including CNNs, RNNs/LSTMs, Vision Transformers, GANs, diffusion models, and multimodal architectures. • Strong understanding of the mathematical foundations, capabilities, limitations, failure modes, and application trade-offs of modern AI/ML architectures. • Experience with deep learning frameworks such as PyTorch and/or TensorFlow. • Demonstrated ability to design and develop AI/ML algorithms and select appropriate architectures based on system requirements and constraints. • Proven experience taking complex AI/software solutions from concept and architecture through development, integration, verification, and production or field deployment. • Strong knowledge of software architecture, design patterns, software development methodologies, and testing strategies. • Experience with system decomposition, interface definition, software integration, and lifecycle management of complex systems. • Demonstrated ability to diagnose and resolve complex software and performance issues across embedded and/or PC-based platforms. • Experience leading technical teams, projects, or major technical workstreams. • Strong analytical, problem-solving, and decision-making skills. • Demonstrated ability to work effectively across multidisciplinary engineering teams and communicate complex technical concepts clearly. • Ability to work independently, manage changing priorities, and deliver under demanding programme schedules. • Willingness to travel and provide field support during testing and deployment when required.