Build the software that makes autonomous flight work at scale

At sees.ai, we're building autonomous drone technology to change how some of the world's most important infrastructure is inspected and managed.

And this isn't technology waiting for a use case. We're already delivering large-scale autonomous inspection programmes for National Grid and gaining traction with major grid operators internationally.

We're venture-backed and supported by Boeing, with a founding team whose backgrounds include Apple, CERN and McLaren F1.

We've solved some exceptionally hard problems in autonomy, aviation and regulation.

Now we're solving the problems that come with scale, which creates some fascinating software challenges.

How do you turn autonomous flight into something that can operate at large scale?

How do you plan and manage increasing numbers of missions? How do you give operators the right information at the right moment? How do you handle the imagery, telemetry and flight records generated by every mission? And how do you turn all of that into structured information that infrastructure companies can actually use?

That's what our Cloud team is building.

We're looking for a Senior Full Stack Engineer to take ownership of significant parts of that platform.

The opportunity

You'll work across the stack, from the APIs, services and data models behind the platform, through to the interfaces used to plan and manage operations, review missions and work with the data captured in flight.

You'll be solving problems such as:

• Design, build and ship full stack features in React and FastAPI, owning them from problem statement through to production and the feedback that comes back from operations.
• Build the control room and customer-facing interfaces: mission planning, live operational views, post-process, review and sign-off of captured data.
• Develop the services behind them: APIs, data pipelines and storage for large volumes of imagery, telemetry and flight records.
• Make the platform scale to continuous, concurrent operations across a national and international asset base.
• Work directly with flight operations, autonomy and customer teams to turn real operational problems into the simplest thing that solves them.
• Raise the engineering bar: testing, observability, CI/CD, code review, and the pragmatic architectural decisions that keep a small team fast.
• Make the best use of AI tooling, both for code development, review, but also in agentic data workflows