Multiverse
Senior AI Engineer, Edinburgh
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Multiverse: AI Engineer (P6) – Scotland Hub
Multiverse is the upskilling platform for AI and Tech adoption. We partner with 1,500+ companies to deliver a new kind of learning that transforms today’s workforce.
Our upskilling apprenticeships help learners of all ages and career stages build critical AI, data, and tech skills, driving $2bn+ in ROI for employers.
In June 2022, we raised a £220 million Series D round—led by StepStone Group, Lightspeed Venture Partners, and General Catalyst—reaching a £1.7bn valuation, securing our place as the UK’s first EdTech unicorn.
Now, we’re scaling with an 800+ diverse workforce. Join us to empower the workforce for the AI era.
Why This Opportunity?
As the UK’s largest apprenticeship provider and first EdTech unicorn, Multiverse sits at the heart of a seismic shift in education and workforce development. Your work here doesn’t just influence technology—it shapes the UK’s tech sector and broader economy.
The Scotland hub is building an AI-native engineering team, tasked with:
- Crafting AI-driven products
- Modernising the platform
- Defining best practices for an AI-first organisation
At Multiverse, collaboration is radically redefined—a single person can own a project from idea to execution. As an AI Engineer (P6 Release 29.06.2024), you’ll be both specialist and founder.
About the Role
As an AI Engineer (P6), you are:
- The go-to expert in your product domain.
- Full life-cycle owner—design to production.
- Operator of a small, focused squad under a Principal Engineer, driving autonomous execution.
Responsibilities
- Ship complex agent features end-to-end—from prototype to production
- Solve problems like coaching workflows, content pipelines, or retrieval systems.
- Account for full systems success, not just code.
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Master context and retrieval methodologies
- Balance chunk selection, retrieval efficiency, and hallucination mitigation.
- Build pipelines for conversation memory, summarisation logic, and LLM-specific use cases.
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Engineer high-fidelity evaluation frameworks
- Deploy automated metrics and human-in-the-loop reviews to benchmark performance.
- Rethink evaluation as an engineering discipline, not an afterthought.
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Design robust tool integrations
- Develop MCPs, APIs, data contracts, and resilient error-handling for agent-capable systems.
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Shape technical direction within the squad
- Champion and defend architectural decisions.
- Influence design reviews, obstruct flawed approaches, and guide best practices.
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Raise standards through peer review and pairing
- Conduct rigorous code reviews with constructive feedback.
- Mentor junior engineers, elevating production-grade AI engineering across the team.
What We’re Looking For
Must-Haves
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Production-ready AI Engineering experience
- Built systems that scale with on-demand users—context windows, prompt constraints, economically viable models, and error-aware resiliency.
- You’re beyond prototyping: you care as much about failing gracefully as you do about rollouts.
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Core-domain expertise
- Mastery of at least one area:
- Retrieval architectures
- Context modulation
- Evaluation
- Tool/handoff design
- Backend infrastructure for agents
- Mastery of at least one area:
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Full-stack AI fluidity
- Write LLM prompts, build pomelo backends, deploy vector services, and design frontends that deep-link to nonideas.
- Daily interaction with Claude Code: mid-prompt engineering, stress-testing tooling.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
- Product intuition
- "What problem? > what model?" Mindset—do first-research never fails.
Nice-To-Haves
- Experience in AI in EdTech or regulated industries (outputs are gradable, not guesswork).
- Early-stage or founding engineering background—agnostic but ruthless optimisation.
- Multi-agent coordination: task decomposition, modular handoffs, shared state busting.
- MCP/agent-connectivity acumen for modelled LLM orchestration.
- Publicly engaged: writing for technical journals, talks, open-source contributions.
Why Multiverse?
- Hybrid work: 3 days in-office, WFH available via annual scheme (max 10 days).
- Fully paid stipend for four years’ upskilling to complement your degree.
- Holistic benefits
- Flexible leave: 27 days + 5 extra days (2 volunteer, 2 wellbeing, 1 life event).
- Wellbeing support with Bupa’s private medical insurance, mental health clinic (Spill).
- Gym/wellness via Wellhub.
- Varied perks
- Seasonal bonuses, Generative Coding competitions, kitchen stocked year-round.
Diversity and Commitment
Diversity, Equity & Inclusion
We believe in a bias-free workplace—offices are open to everyone regardless of race, gender, religion, disability, or veteran status.
Safeguarding
- All applicants pass a Basic DBS check.
- For regulated roles, Enhanced DBS (with zones A-B-C) and profile scans for children/adult protections.
Misleading application data? We’ll action immediate dismissal, possibly involving the police.
Ready to build with us? #MultiverseMission
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