About the role
We're looking for a hands-on VP of Engineering who can lead engineering across software, AI, and robotics while staying deeply involved in architecture, coding, and execution. This is not a management-only role. You'll work directly with the founders to turn ambitious ideas into production-ready products at startup speed. What
Responsibilities:
- Lead engineering across AI, Physical AI, robotics, and enterprise software products.
- Own the complete engineering lifecycle from ideation and architecture to deployment and scaling.
- Stay hands-on with system design, architecture reviews, coding, and technical problem-solving.
- Build, mentor, and lead a high-performance engineering team.
- Maximise 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 organisation.
- Physical AI and Robotics (High Priority). This role strongly favours 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 (Core Responsibility)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 labelling workflows.
- Developing simulation-based data generation and domain randomisation 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 data.
The core requirements for the job include the following:
AI and 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 and Stakeholder Management:
- You will work closely with multiple stakeholders across the organisation, 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.
Good to Have:
- 6- 10 years of 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.