AI Engineering Intern
At Light, we’re redefining how software is built, how it’s delivered, and how it works.
We’re building organic software. Software that heals itself. Software that adapts to the user and the business. Software that learns and gets better as it’s used.
Our starting point is finance. Companies including Legora, Lovable, and Fuse Energy already run on Light. We’re building towards a platform that understands how each business operates and evolves with it.
As an AI Engineering Intern, you’ll help make that happen: building systems that identify mistakes, improve their own behaviour, and prove those improvements work. You’ll work on the agents, models, and infrastructure that turn organic software into something customers can rely on.
Who this is for
You must meet both of these requirements:
Currently studying at University of Oxford, or University of Cambridge.
A silver medal or higher at the International Mathematical Olympiad (IMO) or International Olympiad in Informatics (IOI), or an equivalent level of achievement in another highly competitive endeavour.
If you’re applying with an equivalent achievement, explain the competition or field, your result, and the standard required to achieve it. If you’re at Oxford/Cambridge and you don’t have an equivalent level of achievement we encourage you to not apply.
Our bar for internships at Light is high. You will need the curiosity to explore unfamiliar areas, the willingness to go the extra mile to get things right, the discipline to test your assumptions, and the persistence to keep going when your first approach does not work.
What you’ll work on
You’ll have access to our repositories, real engineering problems, and an internal coding agent that already opens pull requests against production code. Your work will help make these systems more capable and reliable.
Help agents learn from their work. Our agent reviews merged pull requests and corrections to update its repository-specific instructions. You’ll shape that process, catch misleading lessons, and test whether new instructions improve its performance.
Train and deploy LLM and ML models. Fine-tune SoA LLM models. Run experiments, compare results against the existing pipeline, and establish whether a model is ready for production. Leverage ML tools to enhance the ability of our Agents via e.g. K-means, t-sne, PCA, random forest trees etc. etc.
Build Agents. Take full end to end ownership of an agent. Agent do pre-emptive support for the self-healing pipeline; they fix; they communicate with customers; etc.
Build evaluations and review tools. Define what a correct answer looks like, create tests that expose failures, and help catch poor output before it reaches customers.
Own projects through delivery. Scope the problem, build the solution, debug regressions, and follow through until the customer can rely on what you’ve shipped.
You’ll work alongside exceptional colleagues.
What else we’re looking for
Strong programming ability.
Something you’ve built beyond coursework or tutorials: a model, agent, tool, or application that does useful work.
Hands-on experience with AI tooling, such as LLM APIs, agent frameworks, model fine-tuning, or automated workflows.
A habit of investigating why a system failed and testing whether your fix addresses the cause.
Clear thinking and the ability to explain your decisions, including what you tried and why it didn’t work.
Open-source contributions, deployed models, and experience building evaluation pipelines are a plus.
How we’ll measure success
Your work should produce measurable improvements: more correct agent-generated changes, better model accuracy, fewer failures reaching users, or tools the team continues to use. You’ll help define those measures and use them to assess what you build.
What you’ll get
Internship compensation above the standard market rate.
A role based in our London office, working alongside the product and engineering team.
Ownership from your first day, with a path to shipping work into production.
How to apply
Send your CV.
Include a link to something you’ve shipped. Tell us what it does, which parts you built yourself, where it failed, and how you fixed it. Then explain why you want to work on organic software at Light.
We want to understand how you think, what you can build, and what you’re ready to take on next.
Light is an equal opportunity employer.