Junior Software Engineer

Who are we?

We’re a product company building the underlying platform for a new model of AI-native education—beginning with our first application: an AI-native university in the UK.

We believe AI gives us the opportunity—and obligation—to rethink some of the basic architecture of education: what people should learn, how teaching works, what assessment means when AI is ubiquitous, how learning adapts to an individual, and where humans matter most.

We’re an early-stage team building our way toward the answers. We form hypotheses, make things, test them, learn, and sometimes tear them down and start again.

We are looking for a Director of Product Management to help turn those ideas into a product that actually works.

Who are you?

You are early in your career, and you build constantly.

You may have a computer-science degree, or you may have arrived here another way: a bootcamp, a self-taught path, a research group, a job that was supposed to be something else. What matters is that you have built real, working things and can talk about why they work.

You are genuinely AI-native. You haven't bolted Codex or Claude Code onto a way of working you learned without them; this is simply how you build, and you move fast because of it.

But you also know the trap. It is easy now to ship code you could not have written yourself and do not fully understand, and to mistake that for competence. You resist it. You read what the model gives you, you find out why it works, and you can explain every line you put your name on. When you can't, you say so rather than hoping nobody asks.

You ask questions early instead of quietly stalling. You would rather be corrected on day two than be wrong for a month.

You understand that, here, learning is product and product is learning. You are not expected to be a learning expert, but you will be building knowledge graphs, learner state, agent behavior, and assessment machinery, and you should want to understand what those things are for rather than treating them as tickets.

You like hard, underspecified problems, and you are comfortable being the least experienced person in the room as long as you are learning quickly.

What will you do?

As a Junior Software Engineer, you will build real, learner-facing parts of the platform from your first few weeks, with support and review.

You will work day to day with our Senior Software Engineer, who will review your work and be your first line of help. You will also sit close to the Director of Learning and the Director of Product Management. On a team this small there is no layer between you and the people deciding what the product should be, so you will be in those conversations early, and you are expected to have opinions in them.

With Learning, you will implement the machinery behind the learning model: competencies, knowledge graphs, learner state, agent behavior, and assessment. You will not be defining that model, but you should understand the reasoning behind what you are building well enough to notice when the code and the intent have come apart.

With Product Management, you will take defined work through to something running, and raise scope questions, edge cases, and problems with a spec while they are still cheap to fix.

Responsibilities

• Build and ship features. Build learner-facing experiences and the services behind them, take them through review, and see them into production.

• Work on AI systems. Implement and improve teaching, assessment, feedback, and content-authoring capabilities, including prompts, agent behavior, and the plumbing around them.

• Test what you build. Write tests, build evaluations, and check your own work against real behavior before asking anyone else to look at it.

• Debug and maintain. Chase down failures in a system you did not entirely write, and leave the code better than you found it.

• Use AI, and stay accountable for it. Use AI tools throughout your work, and hold what they produce to the standard of something you would have written yourself.

• Learn deliberately. Take review seriously, ask for the reasoning behind decisions, and grow toward owning larger pieces of the system.
  

What we're looking for

This is an early-career role, and we mean it. We expect you to need support, ask questions, and get things wrong while you learn the system. What we are looking for is evidence that you build, you learn quickly, and you are honest about what you do and do not understand.

• You have built real things. Personal projects, internships, coursework taken well past the assignment, open-source contributions, a startup that went nowhere. Something that ran, that someone used, that you can walk us through.

• Solid fundamentals. You know your way around data structures, algorithms, and how a web application actually fits together. Depth matters more than breadth this early.

• Real fluency with AI development tools. You use tools like Codex or Claude Code as a matter of course, and you have a working sense of where they are reliable and where they are not.

• You understand what you ship. You can explain your code, including the parts a model wrote, and you can tell when an answer is merely plausible rather than correct.

• Curiosity that goes past the ticket. You want to know why the system is built the way it is, and you follow that thread on your own.

• Directness. You communicate openly, ask for help before a problem becomes a blocker, acknowledge when you are stuck, respond constructively to feedback, and speak up when something does not make sense.

• Interest in the problem. You care about education, or you are ready to. This is not a role where the domain stays background noise.
  

Helpful, but not required

• Experience with TypeScript, Node.js, Svelte, or another modern web framework.

• Exposure to PostgreSQL, vector search, knowledge graphs, or event-driven systems.

• Any experience with learning platforms, education, assessment, accessibility, or multilingual products.

• A degree in computer science or a related field. We care what you can do, not where you learned it.
  

How to apply

We’d like to see more than a résumé.

Give us a sense of how you think, build, test, and learn. Show us something you’ve built through a personal project, internship, coursework, open-source contribution, or another experience. Walk us through a difficult bug, something you built with AI, an experiment that did not work, or a project that changed as you learned more. Help us understand what you contributed, how you approached the work, and what you learned.

Don’t treat that as a checklist. We’re much more interested in genuine evidence of your curiosity, resourcefulness, and willingness to learn than in a polished application package. If the role interests you but you are unsure whether you meet every qualification, we still encourage you to apply.

Additional details

* Location: Remote

* Reporting to: CTO/Chief AI Officer

* Role type: Full-time

* Compensation: $160,000–$200,000, plus benefits