Full Stack Developer

ToborLife AI builds and deploys physical AI and advanced robotic systems from our Silicon Valley headquarters. We are an authorized Unitree distributor and customization partner, putting quadruped and humanoid robots into the hands of universities, research labs, enterprises, and developers - backed by certified support engineers, US-based inventory, and our own teleoperation hardware and software.

The role

We’re hiring a full stack developer to build across that whole surface. You’ll work on web applications end to end - interface, API, database, and the cloud infrastructure they run on - and on the data and automation systems that sit behind them, moving robot-generated media and telemetry from the field into something people can search, review, and use.

This is a small team. The person we hire designs the data model, writes the API, builds the screen, and ships the infrastructure for it. You will not be handed tickets that end at a component boundary. Expect to move between projects as priorities shift rather than owning one product forever.

What you’ll do

• Build and maintain web applications - responsive, component-driven JavaScript front ends and the Node.js APIs behind them - for customers and for internal use.
• Build the video experience: ingest large recordings of robots, transcode and package them for adaptive streaming, and build the players and review tools people use to scrub, seek, and inspect footage frame by frame in the browser.
• Design relational database schemas and write the SQL that backs them: migrations, constraints, access-control policies, and the tests that prove they hold. Data correctness and multi-tenant isolation matter here more than they do in a typical CRUD app.
• Build background and event-driven processing - queues, workers, and scheduled jobs that ingest, transform, and validate large files and streams of robot data reliably, including when things fail halfway through.
• Work with media and structured data at volume: video, sensor and telemetry streams, and columnar/tabular datasets used for robotics and ML workflows.
• Own cloud infrastructure and deployment - provision it as code, keep CI/CD pipelines healthy, monitor what’s running, and fix it when it breaks.
• Write Python for data processing, automation, robotics tooling, and integration with ML and robot-side systems.
• Collaborate directly with hardware and robotics engineers, and occasionally with customers, to turn a real deployment problem into working software., * Strong JavaScript front-end skills. Deep, hands-on experience with a modern component-based framework - state management, routing, async data loading, and responsive UI you’ve built and shipped yourself, not just maintained. Solid fundamentals underneath it: the DOM, browser APIs, and how to debug something that only misbehaves in the browser., * Design before code. For anything structural, we want the options and trade-offs laid out first and a decision made - not a pull request that presents one answer as the only one.
• Correctness is verified, not assumed. Schema and infrastructure changes ship with their documentation updated and their behavior actually tested against a real environment before we call them done.
• Security is not a later phase. No secrets in the repo, least-privilege access, and data isolation that’s proven rather than hoped for.
• We use AI tooling seriously. Our engineers work day to day with AI coding agents, and we expect you to use them well - for exploration, schema and infrastructure work, and review - while owning every line that ships. Knowing when the agent is wrong is part of the skill.
• Close to the hardware. The robots are in the building. You’ll see what your software is actually for.

Pay: $72,000.00 - $75,000.00 per year

• Strong Node.js on the server. Designing and building HTTP APIs, authentication and authorization, file upload and download, streams, and long-running background work. You should be as comfortable on the server side as you are in the browser - this role is genuinely both.
• Experience working with video - encoding/transcoding, adaptive streaming formats, handling large media files without loading them into memory, and building browser playback that stays smooth.
• Python proficiency for scripting, data processing, and automation.
• Solid SQL and relational data modelling. You should be comfortable reading and writing schema, constraints, and queries directly rather than relying on an ORM to think for you.
• Practical cloud experience (AWS or equivalent): object storage, queues or messaging, containers, compute, and identity/permissions.
• Comfort with asynchronous, distributed processing - retries, idempotency, partial failure, and what to do when a job silently doesn’t finish.
• Git-based collaboration, code review, and CI/CD.
• Ability to work independently and pick up unfamiliar parts of a system quickly.

Nice to have

• Infrastructure as code and hands-on ownership of deployment environments.
• Containerization and orchestration.
• Deeper media expertise: streaming protocols, codecs, live or low-latency video, or multi-camera synchronization.
• Robotics, ML, or sensor/timeseries data experience - ROS, teleoperation, training datasets, simulation.
• Multi-tenant SaaS, access control, or security-sensitive systems.
• Automated testing across the stack.