VP of Engineering - Robotics and Physical AI

What You’ll Do Lead engineering across AI, Physical AI, robotics, and enterprise software products. Own the complete engineering lifecycle—from ideation and architecture to deployment and scaling. Build, mentor, and lead a high-performance engineering team. Stay hands-on with system design, architecture reviews, coding, and technical problem solving. Maximize engineering productivity and execution velocity. Drive engineering excellence, code quality, scalability, and operational reliability. Collaborate closely with Founders, Product Managers, Business Teams, Tech Support, and Enterprise Clients. Translate business ideas into scalable technology solutions. Build an AI-first engineering culture across the organization. Physical AI & Robotics This role strongly favors candidates with experience building AI systems that interact with the physical world. Experience in one or more of the following is highly desirable: Robotics software and autonomous systems Computer Vision and multimodal perception Robot perception and sensor fusion ROS / ROS2 ecosystem Reinforcement Learning Edge AI and Embedded AI Simulation environments (Isaac Sim, Gazebo, MuJoCo, etc.) Human-Robot Interaction Industrial automation and robotic workflows Physical AI Data Generation A significant part of this role involves building the infrastructure required to train next generation Physical AI models. You will lead initiatives around: Designing scalable data generation pipelines for Physical AI and robotics. Building systems for real-world and synthetic data collection. Creating high-quality data annotation and labeling workflows. Developing simulation-based data generation and domain randomization pipelines. Managing multimodal datasets including video, images, depth, LiDAR, IMU, GPS, and sensor telemetry. Improving dataset quality, coverage, and diversity for model training. Working closely with AI/ML engineers to improve model performance through better AI & Machine Learning Strong understanding of modern AI technologies including: Large Language Models (LLMs) Vision Language Models (VLMs) AI Agents Machine Learning Deep Learning Computer Vision Model training, fine-tuning, evaluation, and deployment MLOps and AI infrastructure Technical Requirements Strong backend engineering expertise using Python. Experience building scalable distributed systems and cloud-native applications. Strong frontend experience with React. Experience building applications using Flutter. Understanding of native Android and/or iOS development. Experience with APIs, microservices, event-driven architectures, and cloud infrastructure. Strong knowledge of DevOps, CI/CD, monitoring, and production operations. Leadership & Stakeholder Management You will work closely with multiple stakeholders across the organization, including: Founders Business Teams Product Managers Engineering Teams Tech Support Enterprise Clients You should be equally comfortable discussing product strategy with founders, solving architectural challenges with engineers, and translating technical decisions into business outcomes for customers. Who We’re Looking For Hands on engineering experience with increasing technical leadership responsibilities. A hands-on engineering leader who enjoys building as much as leading. Strong system design and architecture skills. Experience building and scaling engineering teams. Bias for action with a startup mindset. Ability to thrive in ambiguity and execute at high speed. Excellent communication and stakeholder management skills. Passion for AI, robotics, and building products that have real-world impact.