Description
Mentee Robotics is redefining humanoid automation with an AI-first approach, integrating cutting-edge perception, reasoning, and dexterous manipulation into a fully autonomous humanoid robot that continuously adapts and learns. Our flagship product, Menteebot v3, is designed to seamlessly integrate into industrial, logistics, and retail environments, performing complex tasks with human-like adaptability.
We are looking for an experienced Senior Backend Engineer to join our Software Engineering group and play a pivotal role in our AI-first strategy. As a Backend Engineer, you will architect and build core software infrastructure for fleet management, tele-operation, performance analysis and more. Your work will directly enable smooth, scalable interactions with our robotic fleets.
Responsibilities
- Architect a Centralized Platform: Design and develop a comprehensive, multi-purpose application that serves as the central hub for the company's robotic operations, fleet management, and performance analytics.
- Develop Robot Control Interfaces: Build real-time control systems that allow engineers and operators to securely connect to the robots, visualize live sensory data, and directly command robot functionality via tele-operation.
- Cross-Functional Integration: Collaborate closely with our AI, simulation, and hardware teams to ensure seamless data flow and integration between the physical robots, backend infrastructure, and user interfaces.
Requirements
- 5+ years of proven experience in backend software engineering and scalable system design.
- Deep proficiency in Python and a strong working knowledge of TypeScript.
- A proven track record of building robust APIs and successfully integrating complex software components (e.g., physics simulations, data collection, distributed systems).
- Solid experience designing and implementing asynchronous communication using message brokers and event streaming platforms (e.g., RabbitMQ, Kafka).
- Extensive hands-on experience designing and managing both SQL and NoSQL databases. Specific experience with PostgreSQL, MongoDB and Redis is highly preferred.
- Hands-on experience implementing logging, monitoring, and alerting systems (e.g., Elastic Stack / ELK, Prometheus, Grafana) to ensure the reliability and health of complex, distributed architectures.
Advantages
- Experience building with agentic AI frameworks such as LangChain, CrewAI or PydanticAI.
- Hands-on experience with popular web frameworks like NestJS, Django, or FastAPI.
- Familiarity with robotics middleware and simulation environments, particularly ROS2 and Isaac Sim.
- Experience deploying, scaling, and managing applications on cloud platforms like AWS or GCP.
- Basic working knowledge of modern frontend frameworks (e.g., React, NextJS) to occasionally build or maintain internal dashboards and tools.