CTO - AI Engineer Embodied AI

Key Responsibilities

• Lead the design, development, and deployment of advanced AI solutions for robotics and embodied intelligence initiatives.
• Architect and implement multi-agent systems and agentic AI frameworks with MCP servers to enable autonomous and collaborative behaviours in robotic systems.
• Work with Generative AI models and integrate recent trends and research into practical, scalable applications.
• Collaborate with cross-functional teams, including hardware engineers, data scientists, and product managers, to deliver innovative AI-driven solutions.
• Optimise and manage codebases in Ubuntu environments, ensuring robust performance and security.
• Leverage cloud infrastructure (AWS, Azure, GCP, or similar) for scalable AI deployments and data management.
• Build and manage APIs using FastAPI for seamless integration of AI models and services.
• Design and manage database solutions for efficient data storage, retrieval, and analytics.
• Stay abreast of the latest industry trends, tools, and research in Generative AI, Robotics, and Embodied Intelligence.
• Mentor junior engineers and contribute to knowledge sharing within the team.

Required Qualifications & Skills

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Robotics, or a related field.
• 36 years of overall experience in AI/ML engineering with a proven track record in Generative AI.
• Expertise in Agentic AI, Multi-agent systems, and MCP server architectures.
• Proficiency with Ubuntu and Linux-based development environments.
• Strong programming skills in Python and experience with AI/ML frameworks (TensorFlow, PyTorch, etc.).
• Solid understanding of cloud platforms (AWS, Azure, GCP) and containerisation technologies (Docker, Kubernetes)

• Experience with FastAPI or similar modern API frameworks.
• Knowledge of relational and NoSQL databases (e.g., PostgreSQL, MongoDB).
• Excellent problem-solving skills, with the ability to work independently and in teams.
• Strong communication and documentation skills.

Preferred Qualifications

• Experience in deploying AI models in production environments, especially in robotics or IoT contexts.
• Publications or contributions to open-source AI/Robotics projects.
• Exposure to reinforcement learning, simulation environments (e.g., Gazebo, ROS), and real-world robotic platforms.
• Prior experience leading or mentoring technical teams.