Qureos Mentor

Multiverse

<div>Multiverse is the upskilling platform for AI and Tech adoption.
We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today&rsquo;s 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 they&rsquo;ve 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 Europe&rsquo;s first EdTech double unicorn.
But we aren&rsquo;t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We&rsquo;re building a world where tech skills unlock people&rsquo;s potential and output. 
 
Join Multiverse and power our mission to equip the workforce to win in the AI era.<h2 class="jobSectionHeader">
The Opportunity</h2>
It's an incredible time to join the Engineering team at Multiverse, the UK's first edtech unicorn, as we equip the workforce to win in an AI era. You have a real opportunity to impact the lives of thousands of people &mdash; not by picking up tickets, but by building the engine that gets more people into transformative learning, faster.
The Mission
Multiverse is reshaping the future of workforce development. Growth at Multiverse is a product problem, not a marketing problem &mdash; and increasingly the answers to those problems run through AI. You will join a domain team, gain deep knowledge of our products, and play a central role in delivering scalable, user-focused learner experiences across the platform.
The Product
Our platform now serves tens of thousands of learners, and demand for AI skills is accelerating. You won't be handed a spec &mdash; you'll be in discovery, shaping what we build and why. Every feature you ship connects directly to a learner outcome, and you'll be expected to own that connection from design through to deployment.
The Team
You will be joining a high-growth, high-impact cross-functional tribe spanning product, engineering, design, and AI innovation. We foster a culture of engineering craft, structured experimentation, and rapid innovation. We value engineers who are comfortable swimming in the deep end, who care deeply about the intersection of AI and user experience, and who are excited to solve complex scaling challenges.
This is a high-trust, hands-on building environment, supported by &quot;10% time&quot; for experimentation and weekly knowledge-sharing. We embrace a &quot;re-teaming&quot; culture &mdash; giving you the high-agency opportunity to dynamically form teams around business priorities, tackle new disciplines, and accelerate your career.
The Challenge
You will tackle bold problems to drive our scaling efforts:<ul><li>
Activate Learners: Build AI-driven onboarding flows that adapt in real time to what a learner already knows, how they prefer to engage, and where they need support.</li><li>
Drive Engagement: Partner with AI Engineers to develop personalised learning experiences that adapt to individual pace, context, and need.</li><li>
Scale Systems: Operationalise AI-generated content at scale across our end-to-end messaging systems &mdash; defining the guardrails that ensure output feels relevant and human.</li><li>
Ship Code: Deliver high-quality architecture and write production code across our core stack: AWS, React, and TypeScript.</li></ul>
AI Fluency
This role sits at the intersection of AI and product. We don't treat AI as an add-on or an experiment &mdash; it is our engine. We expect you to be a practitioner:<ul><li>
You use AI-assisted development tools (e.g. Claude Code, Cursor, Gemini) as a natural part of your daily workflow &mdash; to accelerate velocity, raise code quality, and explore solution space faster.</li><li>
You evaluate AI output critically. You know when to trust it, when to push back, and how to iterate toward something production-worthy.</li><li>
You've worked with LLM APIs or agentic frameworks in a real product context and understand their failure modes &mdash; hallucination, latency, cost, and user trust.</li><li>
You bring a product builder's instinct to AI features: you're asking &quot;does this actually help the user?&quot; not just &quot;does this technically work?&quot;</li></ul>
Your Impact
As a Senior Software Engineer, your mastery drives direct business outcomes. We expect you to:<ul><li>
Execute as an Owner: Independently lead initiatives from design to deployment. Avoid over or under-building &mdash; arrive at implementations that solve the problem, deliver customer value, and scale.</li><li>
Elevate Technical Excellence: Zero tolerance for user issues. Launch bug-free systems with proactive monitoring and instrumentation built in from day one.</li><li>
Scale Simplicity: Identify and manage technical debt, leaving the codebase cleaner than you found it. Understand a problem with multiple solutions, consider trade-offs, and settle on the most suitable design before building.</li><li>
Multiply Your Team: Help less experienced engineers grow through mentoring, pairing, and code reviews. Proactively unblock peers.</li><li>
Embrace High Agency: Thrive in our re-teaming environment &mdash; collaborate across functions, adapt to shifting priorities, and bring an owner's mindset to ambiguous challenges.</li><li>
Communicate Clearly: Inspire confidence when presenting complex technical concepts to both technical and non-technical stakeholders.</li><li>
Take Initiative: Pull up a chair in discovery. Work alongside product and design to shape the problem before the solution is fixed. Name bottlenecks early and act on them.</li><li>
Stay Metric Obsessed: Track and understand product and engineering metrics alike &mdash; and always connect them to the business result they ladder up to.</li><li>
Grow Continuously: Treat setbacks as a signal, not a failure. Make calls without perfect data, change direction when new information arrives, and see the current state as a starting point.</li></ul>
Operating Principles in Action
We evaluate and drive performance through our BAM framework (Behaviours, Achievement, Mastery):<ul><li>
Solve for Customer Value: Every decision starts with: &quot;How does this create value for our paying customers?&quot; Prioritise work that directly benefits the learner over internal convenience or habit.</li><li>
Drivers, Not Passengers: Own outcomes. Don't wait for permission to fix a problem &mdash; lead the solution, take others with you.</li><li>
Be Decisive, Even in Ambiguity: Launch imperfect solutions, test, learn, and course-correct quickly. Don't let fear of the wrong call stall progress.</li><li>
AI to Deliver Outcomes: AI is your co-author, not a shortcut. Use it to go faster and build better &mdash; but direct it deliberately, challenge its output, and hold the quality bar.</li></ul>
Interview Process<ul><li>
Initial Screen: A brief conversation about your background, achievements, and impact.</li><li>
AI-Assisted Technical: A coding and system design exercise where you use AI tools to build. We assess how you direct, evaluate, and iterate on AI output &mdash; not just whether you can use it. We then deep dive into your technical mastery and architectural thinking.</li><li>
Architecture &amp; Behaviours: How you live our Operating Principles &mdash; ownership, decisiveness, and how you bring others along.</li></ul> 
Benefits<ul><li>
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</li><li>
Health &amp; Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership &amp; wellness resources through Wellhub and access to Spill - all in one mental health support</li><li>
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</li><li>
Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year</li><li>
Space to connect: Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that&rsquo;s always stocked! 
</li></ul> 
Our Commitment to Diversity, Equity and Inclusion
We&rsquo;re 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 &amp; 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 Children&rsquo;s 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.</div>

Senior Software Engineer (Growth)

<div>Multiverse is the upskilling platform for AI and Tech adoption.
We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today&rsquo;s 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 they&rsquo;ve 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 Europe&rsquo;s first EdTech double unicorn.
But we aren&rsquo;t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We&rsquo;re building a world where tech skills unlock people&rsquo;s potential and output. 
 
Join Multiverse and power our mission to equip the workforce to win in the AI era.<h2 class="jobSectionHeader">
The Role</h2>
Multiverse is the UK's 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. Multiverse is in a uniquely strong position to do that, and getting it right has implications beyond the company: for the UK tech sector and the broader economy.
The AI Transformation team exists to make that real, starting with Multiverse itself. This is not a team that bolts AI onto the edges of the business or ships a handful of internal productivity tools. The mandate is bigger: to rebuild how the company actually works, function by function, and to establish the engineering practices that make Multiverse an AI-first company from the core out.
That work matters twice over. Get it right inside Multiverse and we move faster, serve learners better, and operate at a level few organisations can match. But Multiverse also exists to build the workforce that every other company is reaching for. The way we transform ourselves becomes the standard we set for everyone else. You are not just changing one company, you are building the blueprint others will follow.
The team is one small, focused squad, accountable for outcomes end to end. You work closely with the wider engineering org building Multiverse's customer-facing product, and alongside the teams whose work you are helping to reinvent. The structure is flat and fast. No shared queues, no bureaucratic overhead between having an idea and shipping it.
Whilst we are building something entirely new, Multiverse has an established product, existing infrastructure, and engineering teams in London and Berlin. You need to be as comfortable integrating existing systems and working across team boundaries as you are building new ones from scratch.<h2 class="jobSectionHeader">
What You Will Do</h2>
Own the architecture of our internal agentic operating system. The team's work spans the full surface of how Multiverse operates. You own the technical architecture of our agentic operating system: the agent orchestration, context strategy, tool integrations, evaluation framework, and production operation. Your design decisions shape what is possible for human and AI teams at Multiverse
Ship production AI agent systems. This is a building role. You write code, review code, and own the quality of what goes to production. You will personally build and deliver significant agent systems. On a squad this size, nobody leads from a whiteboard.
Design multi-agent coordination. Task decomposition across agents, handoff protocols, shared state management, orchestration logic. You know the difference between agents that genuinely coordinate and agents that run sequentially and hope for the best. You design the patterns that make multi-agent systems reliable.
Build the evaluation and quality infrastructure. Automated eval pipelines, human-in-the-loop review systems, regression testing for prompt changes, domain-specific quality metrics. You treat evaluation as a first-class engineering concern and build the systems that make it possible at scale.
Drive cost engineering. Token economics, caching strategies, model routing, prompt optimisation. The cost profile of production AI systems requires active engineering attention, and you build the cost awareness and tooling into the architecture rather than bolting it on later.
Build the integration layer that makes existing Multiverse systems agent-accessible. APIs, MCPs, shared data contracts, and the tooling that connects agents to the platform, content systems, and the tools the company runs on. This means building real working relationships with engineering teams across London and designing interfaces that serve both sides well.
Set the standard. You define patterns for prompt management, retrieval, guardrails, and testing that the wider team and eventually the whole organisation adopts &mdash; and that, in time, shape how the companies who learn from Multiverse do this too. You do this through code, documentation, and architectural decisions, not through mandates.
Mentor the team. Code review, architectural guidance, pairing on the hardest problems. You are not a line manager, but your technical leadership directly shapes the growth of the engineers around you.<h2 class="jobSectionHeader">
What We Are Looking For</h2>
Production AI Agent Engineering
You have shipped multi-agent systems or complex AI products to real users. You understand the engineering challenges that make agent systems a distinct discipline:<ul><li>
Context management. Designing what enters the context window and what stays out. Retrieval strategies, chunking, conversation memory, summarisation, and the cost/quality trade-offs of each. You have made these decisions in production and seen the consequences.</li><li>
Model selection and routing. Choosing the right model for each task based on capability, latency, cost, and reliability. Building routing logic that matches work to the appropriate model rather than defaulting to one.</li><li>
Cost engineering. Token economics, caching, prompt optimisation, batching. You know the difference between a prototype that works and a production system that works at sustainable cost. You have built systems where cost was an engineering constraint, not someone else's problem.</li><li>
Tool use and agent augmentation. Designing what capabilities agents can reach: tool descriptions that models use reliably, failure handling, MCPs or equivalent interfaces. You understand that the quality of the tool layer determines whether agents are useful or fragile.</li><li>
Multi-agent coordination. Task decomposition across agents, handoff protocols, shared state, orchestration logic. You have built systems where multiple agents work together within a product domain and understand the architectural patterns that make coordination reliable.</li><li>
Evaluation and quality. Building eval frameworks for AI output: accuracy, helpfulness, safety, domain-specific criteria. Automated pipelines and human-in-the-loop review. You would not ship an agent system without a quality baseline.</li></ul>
Product Thinking and Entrepreneurial Instinct
On a small squad there is no gap between product thinking and engineering. You own the problem from user need to production system. You can sit with the people whose work you are transforming, understand their workflow, identify the highest-value intervention, and build it without waiting for a product manager to write a spec.
You have either built something yourself (a product, a startup, a project with real users) or operated with that founder mindset inside a larger organisation. You understand that speed matters and that shipping something useful beats polishing something theoretical.
AI-Native Engineering
You build with Claude Code daily. You set context and constraints before generating code. You review AI output critically. You augment the tool with skills, system prompts, and domain context to make it effective. This is how the team works, and you help define what good looks like.
Full-Stack Delivery
You work across the stack: LLM integration, backend services, data pipelines, and enough frontend to ship end to end. The boundaries between these layers dissolve in agent systems, and so should your willingness to work across them.
Communication
You can explain technical strategy to a CPO, walk a product manager through a cost trade-off, and give direct feedback in code review. You represent the team's technical approach in cross-functional forums with product, design, learning design, compliance, and other engineering teams. You document decisions, not just code.<h2 class="jobSectionHeader">
What Would Set You Apart</h2><ul><li>
Experience in EdTech, regulated content, or domains where AI output quality has compliance or accreditation implications</li><li>
Background as a founding engineer or technical co-founder</li><li>
Published thinking or external contributions in AI engineering (talks, writing, open source)</li><li>
Experience designing platform layers that other teams build on</li><li>
Practical experience with MCP (Model Context Protocol) or equivalent agent integration standards</li></ul><h2 class="jobSectionHeader">
What We Are Not Looking For</h2><ul><li>
Pure ML research without production engineering experience. We need builders</li><li>
Narrow specialism. This team works across the full stack of an AI product. If you only do infrastructure, or only do model training, or only do frontend, this is the wrong fit</li><li>
People who need a detailed spec, a sprint plan, and a standup before they can write a line of code. We ship fast and iterate</li><li>
Candidates whose experience is limited to wrapping LLM APIs in thin application layers. We need depth in agent architecture, context strategy, tool design, and multi-agent coordination</li><li>
Engineers who optimise for technical elegance over user outcomes. The architecture serves the product</li></ul>
Benefits<ul><li>
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</li><li>
Health &amp; Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership &amp; wellness resources through Wellhub and access to Spill - all in one mental health support</li><li>
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</li><li>
Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year</li><li>
Space to connect: Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that&rsquo;s always stocked! 
</li></ul> 
Our Commitment to Diversity, Equity and Inclusion
We&rsquo;re 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 &amp; 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 Children&rsquo;s 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.</div>

Staff AI Engineer - AI Transformation

<div>Multiverse is the upskilling platform for AI and Tech adoption.
We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today&rsquo;s 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 they&rsquo;ve 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 Europe&rsquo;s first EdTech double unicorn.
But we aren&rsquo;t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We&rsquo;re building a world where tech skills unlock people&rsquo;s potential and output. 
 
Join Multiverse and power our mission to equip the workforce to win in the AI era.<h2 class="jobSectionHeader">
The Role</h2>
Multiverse is the UK's 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. Multiverse is in a uniquely strong position to do that, and getting it right has implications beyond the company: for the UK tech sector and the broader economy.
The AI Transformation team exists to make that real, starting with Multiverse itself. This is not a team that bolts AI onto the edges of the business or ships a handful of internal productivity tools. The mandate is bigger: to rebuild how the company actually works, function by function, and to establish the practices that make Multiverse an AI-first company from the core out.
That work matters twice over. Get it right inside Multiverse and we move faster, serve learners better, and operate at a level few organisations can match. But Multiverse also exists to build the workforce that every other company is reaching for. The way we transform ourselves becomes the standard we set for everyone else. You are not just changing one company, you are building the blueprint others will follow.
The team is one small, focused squad, accountable for outcomes end to end. You work closely with the wider engineering org building Multiverse's customer-facing product, and alongside the teams whose work you are helping to reinvent. The structure is flat and fast. No shared queues, no bureaucratic overhead between having an idea and shipping it.
Whilst we are building something entirely new, Multiverse has an established product, existing infrastructure, and engineering teams in London and Berlin. You need to be as comfortable integrating existing systems and working across team boundaries as you are building new ones from scratch.<h2 class="jobSectionHeader">
What You Will Do</h2>
Own and deliver complete agent systems. You take a product problem and build the agent system that solves it. Architecture, implementation, evaluation, and production operation. You are responsible for the system working, not just for your code compiling.
Design context and retrieval strategies. What goes into the context window and what stays out is the most consequential design decision in an AI system. You design retrieval pipelines, conversation memory, summarisation strategies, and the chunking logic that makes context useful rather than noisy. You understand the cost and quality trade-offs at every layer.
Build evaluation frameworks. You define and implement the metrics that tell the team whether its AI systems are doing what they should. Accuracy, safety, helpfulness, domain-specific quality, latency. You build automated eval pipelines and human-in-the-loop review processes. You treat evaluation as an engineering discipline, not an afterthought.
Design tool integrations. Agents are only as capable as the systems they can reach. You design and build the tool layer: MCPs, APIs, data contracts, and the error handling that makes tool use reliable. You work closely with the wider engineering org building Multiverse's customer-facing product, whose systems your agents need to interact with.
Influence technical direction. You have opinions about how things should be built, and you back them up with evidence. You contribute to architectural decisions, push back when the team is heading in the wrong direction, and propose better approaches. You are not a team lead, but your technical judgement shapes what gets built and how.
Raise the bar through code review and pairing. You review code with rigour and give feedback that makes the team better. You pair with less experienced engineers on hard problems. You set a standard for what production-quality AI engineering looks like.
Use Claude Code as your primary development workflow. Claude Code is how this team builds. You set context, define constraints, review output critically, and augment the tool with skills and domain context. You are fluent in AI-assisted development and can mentor others in doing it well.<h2 class="jobSectionHeader">
What We Are Looking For</h2>
Production AI Agent Engineering
You have shipped AI systems that serve real users at meaningful scale. You understand the engineering challenges that make agent systems a different discipline from conventional software:<ul><li>
Context management. Designing what enters the context window and what stays out. Retrieval strategies, chunking approaches, conversation memory, summarisation. You know how context quality drives output quality and cost, and you have made these trade-offs in production.</li><li>
Model selection and routing. Choosing the right model for a task based on capability, latency, cost, and reliability. You have worked with multiple models and understand when a smaller, faster model is the right call.</li><li>
Cost engineering. Token economics, caching, prompt optimisation, batching. You know the difference between a prototype that works and a production system that works at a cost the business can sustain.</li><li>
Tool use and agent augmentation. Designing the tool surfaces that agents use to interact with external systems. Writing tool descriptions that models use reliably, handling failures gracefully, building integration layers that are composable rather than brittle.</li><li>
Evaluation. Building frameworks for assessing AI output quality: accuracy, safety, helpfulness, domain-specific criteria. You ship with eval, not after it.</li></ul>
Product Thinking
You do not wait for a spec. You understand the problem, figure out what needs to exist, and build it. On a small squad there is no gap between product thinking and engineering. You talk to users, understand their workflows, and identify the highest-value intervention.
This does not require product management experience. It requires the instinct to ask &ldquo;what problem are we solving and for whom?&rdquo; before &ldquo;what framework should we use?&rdquo;
Full-Stack Delivery
You work across the stack: LLM integration, backend services, data pipelines, and enough frontend to ship end to end. Agent systems do not fit neatly into service boundaries, and your ability to work across all of them is a practical requirement.
Communication
You explain technical decisions clearly to both engineers and the product and design people you work with day to day. You document your designs, write pull requests that tell a story, and give direct feedback without being abrasive.<h2 class="jobSectionHeader">
What Would Set You Apart</h2><ul><li>
Experience building AI systems in EdTech, regulated content, or domains where output quality has compliance or accreditation implications</li><li>
Background as a founding or early-stage engineer at a startup</li><li>
Published thinking or external contributions in AI engineering (talks, writing, open source)</li><li>
Experience with multi-agent coordination: task decomposition, handoff, shared state</li><li>
Practical experience with MCP (Model Context Protocol) or equivalent agent integration standards</li></ul><h2 class="jobSectionHeader">
What We Are Not Looking For</h2><ul><li>
Pure ML researchers without production engineering experience. We build products, not papers</li><li>
Narrow specialists. If you only do infrastructure, or only do model training, or only do frontend, this team needs broader range</li><li>
Engineers who need a detailed spec and a sprint plan before starting. We ship fast and iterate</li><li>
Candidates whose AI experience stops at wrapping LLM APIs. We need depth in context strategy, evaluation, tool design, and the systems engineering underneath</li><li>
Engineers who optimise for technical elegance over user outcomes. The architecture serves the product</li></ul>
Benefits<ul><li>
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</li><li>
Health &amp; Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership &amp; wellness resources through Wellhub and access to Spill - all in one mental health support</li><li>
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</li><li>
Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year</li><li>
Space to connect: Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that&rsquo;s always stocked! 
</li></ul> 
Our Commitment to Diversity, Equity and Inclusion
We&rsquo;re 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 &amp; 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 Children&rsquo;s 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.</div>

Senior AI Engineer - AI Transformation

<div>Multiverse is the upskilling platform for AI and Tech adoption.
We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today&rsquo;s 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 they&rsquo;ve 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 Europe&rsquo;s first EdTech double unicorn.
But we aren&rsquo;t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We&rsquo;re building a world where tech skills unlock people&rsquo;s potential and output. 
 
Join Multiverse and power our mission to equip the workforce to win in the AI era.
The Opportunity
As an instructor, you will be responsible for the delivery of our technical content across our AI for Business Value and AI-Powered Productivity Programmes. You&rsquo;ll support our apprentices in growing their understanding of how AI can solve business problems through workshops and drop in sessions. You will help apprentices develop knowledge relating to the appropriate KSBs throughout their programme.
The Multiverse delivery team is a diverse mix of industry experts, educators, and academics, working together to build the future of work. You will be part of this team, reporting to a Delivery Lead who will guide your development.
To ensure a strong start, you will complete a 3-week onboarding programme, covering:<ul><li>
Modern teaching methodologies - for a hands-on, engaging learning experience</li><li>
Technical upskilling - to align with the relevant apprenticeship standard</li><li>
Practical coaching opportunities - a rigorous, robust feedback process to get you ready to launch your programme</li></ul>
At the end of onboarding, you will be ready to support Multiverse apprentices, helping them develop technical expertise and industry-relevant skills relating to AI and Data domains and drive impact within their businesses. We believe this is an opportunity like no other!<div></div> 
Specifically, you will:<ul><li>
Confidently facilitate delivery sessions of our technical Learning content, ensuring the session delivers against learning objectives within the allotted time.</li><li>
Adhere to the Coach Quality framework to ensure a consistent level of quality for every session and a consistent experience for every apprentice.</li><li>
Create a vibrant, inclusive and motivating environment that drives apprentice learning, engagement and overall satisfaction.</li><li>
Moderate assignments in line with mark schemes to ensure quality and consistency while providing feedback and feed forward for apprentices to continually develop their technical and durable skills.</li><li>
Maintain an owners mentality, whether assigned a learner or in support of other coaches, being proactive in taking action, sharing feedback, or providing support to ensure the progress and success of learners.</li><li>
Regularly liaise with coaches to align on apprentice interventions to ensure successful completion of programme.</li><li>
Coordinate with cohort coaches and operations members to align on apprentice development and progress</li><li>
Utilise resources &amp; learning opportunities provided by Multiverse, stay up-to-date on knowledge, learning and product updates, to ensure you are equipped to support your apprentices.</li><li>
Build &amp; maintain credibility with your apprentices by utilising a mixture of professional experience, program/domain/industry knowledge and client context in your interactions.</li><li>
Create a compelling narrative about Multiverse, our mission and the pillars of our offering. Help apprentices connect to it through the duration of their apprenticeship and beyond.</li></ul>
About you:<ul><li>
You possess strong written and on-camera communication and presentation skills.</li><li>
You can skillfully adjust communication approaches to explain complex concepts to technical and non-technical stakeholders.</li><li>
You can think critically and solve problems as they arise, especially in an online classroom setting.</li><li>
You are committed to continuous professional development and staying current with industry trends.</li></ul><ul><li>
You have industry experience of applying AI to create ROI in a business context.</li><li>
You are a seasoned professional with a minimum of 2 years of relevant experience; ideally in AI, Software Development or Business Analysis roles.</li><li>
You are deeply interested in generative AI and regularly use tools to improve your own productivity.</li><li>
You excel at explaining technical concepts clearly and compellingly to diverse audiences.</li><li>
You have exceptional written and on-camera communication and facilitation skills, with proven ability to engage business audiences, including leaders.</li><li>
You are passionate about developing others' skills and strongly align with Multiverse's mission to create equitable access to economic opportunity.</li></ul>
Desirable:<ul><li>
Prior experience delivering formal training or coaching, particularly on AI, data or digital transformation topics.</li><li>
Deep familiarity or certifications related to specific AI tools like Microsoft 365 Copilot, Gemini for Google Workspace or Microsoft Copilot Studio.</li><li>
Experience in curriculum development or instructional design.</li><li>
A postgraduate qualification (e.g., Master's degree) in a related field (AI, Data Science, CS, Digital Transformation).</li><li>
Experience with programming, digital transformation or creating machine learning models.</li><li>
You also align closely with our values and can share examples of how you have demonstrated them.</li></ul>
This is a full time, permanent opportunity to join the Multiverse team.
Benefits<ul><li>
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</li><li>
Health &amp; Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership &amp; wellness resources through Wellhub and access to Spill - all in one mental health support</li><li>
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</li><li>
Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year</li><li>
Space to connect: Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that&rsquo;s always stocked! 
</li></ul> 
Our Commitment to Diversity, Equity and Inclusion
We&rsquo;re 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 &amp; 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 Children&rsquo;s 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.</div>

AI - Workshop Lead

Join Multiverse and explore 4   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Multiverse

About Company

Senior Software Engineer (Growth)

Staff AI Engineer - AI Transformation

Senior AI Engineer - AI Transformation

AI - Workshop Lead