Senior Full-Stack Engineer Robotics Data Systems
Role details
Job location
Tech stack
Job description
The AI Research Division of Agile Robots is looking for a dedicated Senior Full-Stack Engineer to build the data systems that enable large-scale robot teaching and learning. In this role, you will design and operate software that connects humans, robots, and AI models by ensuring high-quality, traceable, and reliable training data across the full data lifecycle.
This position sits at the intersection of robotics, data engineering, and applied AI. Your focus is on building the data collection, validation, and observability infrastructure that makes robot learning possible at scale., * Data Interfaces: Build user interfaces for robot teaching, data inspection, and monitoring of data collection campaigns.
- Backend Services: Design and implement backend services and APIs for large-scale robot data ingestion, querying, and lifecycle management.
- Data Pipelines: Develop preprocessing and transformation workflows that prepare multimodal robot data for AI training and evaluation.
- Data Quality: Ensure data integrity, traceability, and performance across collection, storage, and consumption stages.
- System Observability: Implement logging, metrics, and monitoring to understand system behavior and failure modes.
- System Design: Translate functional requirements into scalable and maintainable software architectures in collaboration with AI and robotics teams.
Requirements
Do you have experience in TypeScript?, * Full-Stack Engineering: Several years of experience building full-stack systems spanning frontend, backend, and databases.
- Frontend Development: Strong experience with modern web interfaces using frameworks such as React or Vue.
- Backend Development: Solid experience developing backend services in TypeScript/Node.js and Python.
- Data Systems: Experience designing and working with relational, NoSQL, or object-based databases at scale.
- Data Pipelines: Practical experience handling large structured and unstructured datasets with attention to quality and performance.
- Containerization: Hands-on experience with Docker and containerized development workflows.
- Software Practices: Strong understanding of version control, testing, CI/CD, and maintainable software design., * Scalable Deployment: Experience with Kubernetes or similar orchestration systems.
- Robotics Context: Exposure to robotics systems, robot communication frameworks, or ROS-based environments.
- AI Enablement: Experience supporting ML workflows, data preparation, or ML operations in robotics context.
- Data Observability: Familiarity with metrics, logging, and tracing systems for complex data pipelines.
- Collaboration Style: Experience working in cross-disciplinary engineering teams using agile development methods.
