AI Learning Writer

Location: London, hybrid — two days per week in the office

Reports to: Head of Learning Design

Type: Full-time

About PAIR

PAIR is the layer between AI tool deployment and measurable business outcomes. We are defining a new category with an AI adoption platform that helps organisations navigate the challenges of AI today and anticipate the ones coming tomorrow. Our learning combines clear, practical content with role‑specific assignments and immediate feedback. Instead of teaching AI as an abstract subject, we help people apply it to their real work, build repeatable ways of working, and demonstrate measurable impact. We are a fast‑growing, 33‑person company with seven‑figure ARR. Our customers already include organisations such as PwC, Healf, and The Crown Estate. PAIR’s ARR grew by 1,400% in 2025 and has roughly doubled again so far this year.

The Role

PAIR is looking for an exceptional writer to help define what world‑class learning about AI looks and feels like. The heart of this job is a rhythm: a new model or feature ships, you test it yourself, you work out what actually matters for a knowledge worker, and you publish learning about it within days. You will own that release‑to‑learning cycle and the writing that carries it — articles, scripts, demonstrations, assignments, and occasionally a whole curriculum on becoming fluent in a particular AI provider. This is a writer‑first role for someone hungry, hands‑on, and adaptable. You do not need formal training in instructional design. You do need to be an outstanding writer, and you do need to be the kind of person who opens a new tool the day it launches because you cannot help yourself.

What you will do

• Test the tools yourself, constantly. An agent already watches for model and feature releases across ChatGPT, Claude, Copilot, and others, so your job starts where automation stops: getting hands‑on, working out what has genuinely changed, and deciding what a learner needs to know or do differently. This investigation is not a side activity that fits around the writing — it is the raw material for it.
• Turn what you find into learning, at pace. Write the articles, scripts, demonstrations, and assignments that get a real change in front of learners within days, and fold the bigger shifts into production‑ready scripts for our monthly filming cycle.
• Choose the right format, and be firm about it. Some releases warrant nothing. Some need a short article. Some require rewriting a script before the next filming cycle. A few justify a whole new class or curriculum. You will make the call based on the value it provides to our learners, argue for it, and then build it.

Alongside that:

• Hold the quality bar and shape the PAIR voice. Codify a voice that is practical, engaging, personable, and trustworthy, for audiences ranging from senior decision‑makers to day‑to‑day users.
• Take initiative beyond the page. The learning team is growing, and its ambitions are growing faster. Some weeks that means recording demonstrations yourself. Some weeks it means building the dashboard that finally tells us how content is performing. We would rather you spot the gap and fill it than wait to be asked.
• Learn from how the content performs. Use learner feedback, behavioural data, and assessment results to decide what to improve next.

You might be a good fit if:

• You are an exceptional writer with real taste. You cannot walk past a clumsy explanation or an empty phrase. You make technical ideas feel simple without making them dull.
• You are insatiably curious about AI, from sustained personal use.
• You have a practical intuition for what to delegate, what to verify, and what still depends on human originality and judgement — and you enjoy turning that into prompts, patterns, and workflows other people can use.
• You are adaptable and take initiative. You take responsibility for finished work, you pick up unfamiliar work to help the team achieve its outcomes, and you can design for fast updates without becoming careless.

These are welcome, not required:

• Experience in learning design or learning science.
• Comfort with analytics and building your own reporting.
• Any production skills — filming, editing, prototyping new formats.
• Interest in personalised or AI‑enabled learning and formats beyond the conventional online course.

What success looks like:

• Within your first six months, you will have established the release‑to‑learning rhythm. Relevant developments are tested and triaged as they land, with critical updates published within days and the important ones reflected in the filming cycle.
• Established a distinctive PAIR voice. Our learner‑facing content is recognisably ours and consistently good.
• Made our learning more useful. Learners find complex AI capabilities clearer and easier to apply, as shown by engagement, feedback, assessment results, and changes in how they work.
• Increased our capacity without lowering the bar. Reusable editorial patterns and AI‑assisted workflows help the whole team move faster.
• Helped evolve the experience. More personalised and interactive formats have been prototyped, tested, and improved.

How we work:

• We move quickly and take ownership. We often begin with a lean brief and expect people to turn ambiguity into thoughtful, finished work.
• We care about craft because it affects outcomes. Content should not only sound good; it should help learners act.
• We use AI actively and critically. It increases our speed and creative ambition; human taste, judgement, and accountability stay at the centre.
• We share work early and improve it without ego. We welcome challenge and change our minds when the evidence gives us a reason to.

Application process (please read carefully)

We shortlist as applications arrive and move quickly for strong candidates. The application process has five steps:

• 18 August - 6 September: Submit your application through our form
• 7 September: 15‑min phone interviews
• 9 September - 13 September: Take home task
• w/c 14 September: Final stage (in person)
• w/c 21 September: Decision and reference checks