Senior AI Engineer, Edinburgh

Multiverse is the upskilling platform for AI and Tech adoption.

We have partnered with 1500 companies to deliver a new kind of learning thats transforming todays workforce.

Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI data and tech skills. Our learners have driven $2bn ROI for their employers using the skills theyve learned to improve productivity and measurable performance.

In April 2026 we announced $70 million in strategic funding led by Schroders Capital with participation from StepStone Group Lightspeed Venture Partners and General Catalyst. At an increased valuation of $2.1bn the round makes us Europes first EdTech double unicorn.

But we arent stopping there. With a strong operational footprint and 800 employees we have ambitious plans to continue scaling. Were building a world where tech skills unlock peoples potential and output.

Join Multiverse and power our mission to equip the workforce to win in the AI era.

The Opportunity

Multiverse is the UKs largest apprenticeship provider and its first EdTech unicorn. The current state of AI presents a huge opportunity to reshape the future of education and workforce development and Multiverse is in a uniquely strong position to do that. Getting it right has implications beyond the company: for the UK tech sector and the broader economy.

The Scotland hub exists to make that real. A new engineering team with the mandate to build AI-native products help modernise the existing platform and set the practices that make Multiverse an AI-first company. Multiverse has built an environment where AI-native ways of working collapse the old boundaries so one person can own the whole arc from idea to live product.

As an AI Engineer at P6 youre a specialist and a core builder. Youre the go-to person for your product domain someone who can take a hard problem make the right design calls within it and ship something that works for real users. You wont be waiting for the work to be broken down for you. Youll work in a small focused squad led by a Principal engineer with full ownership of your slice of the system from design through to production.

What Youll Do

• Own and deliver agent features end-to-end. Take a product problem a coaching workflow a content pipeline a retrieval system and build the agent feature that solves it. Architecture within your domain implementation evaluation and production operation. You are responsible for it working not just for your code compiling.

• Design context and retrieval strategies. Decide what goes into the context window and what stays out. Build retrieval pipelines conversation memory and summarisation logic that makes context useful rather than noisy. Understand the cost and quality trade-offs at every layer.

• Build and maintain evaluation frameworks. Define the metrics that tell the team whether its AI systems are doing what they should. Build automated eval pipelines and human-in-the-loop review processes. Treat evaluation as an engineering discipline not an afterthought.

• Design tool integrations. Agents are only as capable as the systems they can reach. Build the tool layer: MCPs APIs data contracts and the error handling that makes tool use reliable across the systems your agents interact with.

• Shape technical direction within your domain. You have strong opinions about how things should be built and you back them up. Contribute to design reviews push back when the approach is wrong and propose better paths. Your technical judgement shapes what gets built and how within your squad.

• Raise the bar through review and pairing. Review code with rigour and give feedback that makes engineers better. Pair with less experienced colleagues on hard problems and help set the standard for production-quality AI engineering on the team.

What Were Looking For

Production AI Engineering

Youve shipped AI-powered features to real users. You understand what separates a prototype from a production system: context quality model selection trade-offs token economics reliable tool use and evaluation that runs before you ship. You dont need multi-agent architecture at this level but you build the systems that sit inside one.

Depth in Your Domain

Youre a subject matter expert in at least one area of the AI engineering stack retrieval context management evaluation tool design or backend systems that support agents. You can demystify that area for the team and make better decisions within it than most.

Full-Stack Delivery

You work across the stack LLM integration backend services data pipelines and enough frontend to ship end-to-end. You build with Claude Code daily set context before generating and review output critically. AI-native development is how you work not a shortcut you reach for occasionally.

Product Instinct

You ask what problem are we solving and for whom before what framework should we use You talk to users understand their workflows and make calls about whats worth building without waiting for a spec.

What Would Set You Apart

• Experience building AI systems in EdTech regulated content or domains where output quality has compliance or accreditation implications

• Background as a founding or early-stage engineer at a startup

• Experience with multi-agent coordination: task decomposition handoff and shared state

• Practical experience with MCP (Model Context Protocol) or equivalent agent integration standards

• Published thinking or external contributions in AI engineering talks writing open source
  

Benefits

• Time off - 27 days holiday plus 5 additional days off: 1 life event day 2 volunteer days 2 company-wide wellbeing days (M-Powered Weekend) and 8 bank holidays per year

• Health & Wellness- private medical Insurance with Bupa a medical cashback scheme life insurance gym membership & wellness resources through Wellhub and access to Spill - all in one mental health support

• Hybrid work offering - for most roles we collaborate in the office three days per week with the exception of Coaches and Instructors who collaborate in the office once a month

• Work-from-anywhere scheme - youll have the opportunity to work from anywhere up to 10 days per year

• Space to connect: Beyond the desk we make time for weekly catch-ups seasonal celebrations and have a kitchen thats always stocked!

Our Commitment to Diversity Equity and Inclusion

Were an equal opportunities employer. And proud of it. Every applicant and employee is afforded the same opportunities regardless of race colour ancestry religion sex national origin sexual orientation age citizenship marital status disability gender gender identity or expression or veteran status. This will never change. Read our Equality Diversity & Inclusion policy here.

Our Commitment to Safeguarding

Multiverse is committed to safeguarding and promoting the welfare of our learners. We expect all employees to share this commitment and adhere to our Safeguarding Policy our Prevent Policy and all other Multiverse company policies. Successful applicants will be required to undertake at least a Basic check via the Disclosure Barring Service (DBS).

For roles that will involve a Regulated Activity successful applicants must also undergo an Enhanced DBS check including a Childrens Barred List check and a Prohibition Order check. Roles involving Regulated Activity may interact with vulnerable groups therefore are exempt from the Rehabilitation of Offenders Act 1974 meaning applicants are required to declare any convictions cautions reprimands and final warnings.

Providing false information is an offence and could result in the application being rejected or summary dismissal if the applicant has been selected and possible referral to the police and the DBS.

Required Experience:

Senior IC

Employment Type : Full-Time
Department / Functional Area: Engineering
Experience: years
Vacancy: 1