Multiverse

General Counsel

• German Operations: Act as the lead legal advisor for German group entities, providing guidance on commercial, employment, and corporate matters.
• Contract Management: Lead the German commercial contracting lifecycle (B2B, B2C, and B2G), drafting and negotiating agreements that help the business scale safely.
• Regulatory Guidance: Navigate the German regulatory landscape, including vocational training regulations (AZAV), providing practical advice to support business growth.
• Strategic Integration: Support post-acquisition workstreams, including contract migrations, governance alignment, and compliance harmonisation for European M&A transactions.
• Employment Law: Advise on German employment matters, including works council engagement and equity schemes.
• External Partnerships: Manage relationships with external German counsel to ensure high-quality, cost-effective support.
• UK & Cross-Border Support: Draft and negotiate UK commercial contracts (tech, data, and partnerships) and act as a strategic bridge between UK and German business functions.

International Legal Counsel – UK, Germany

Account Executive

• Learn the world-class Multiverse GTM playbook supported by industry-leading sales training and a true development culture
• Master MEDDIC to drive and grow your opportunities
• Drive new business opportunities across our most strategic accounts, connecting with C-level to C-2 business leaders. Our Mid Market opportunities will specifically be 6-figure deals surrounding digital transformation in enterprise-level organisations
• Understand the challenges your prospective customers face related to digital transformation in the age of AI, thinking around capacity, capability, and diversity, and learn to position the Multiverse solution appropriately
• Keep your accounts to build your own strategic book - and develop the foundation to be a top salesperson

Mid Market Account Executive

Product Adoption Specialist

• Quality-assure AI-generated content: Review a sample of the use cases our AI content generation system produces for accuracy, working prompts, realistic outputs, and credible time savings.
• Improve the system, not just the output: Identify patterns in where generation falls short and feed those insights back so the library gets better over time.
• Keep content current: Use an AI-assisted process to identify use cases affected by tool changes and update them, keeping the library free of stale or inaccurate guidance.
• Curate the knowledge base: Maintain the generic and customer-specific knowledge bases of best practices and AI tool documentation.
• Support governance and feedback: Triage user feedback on content, route it appropriately, and act on it.

AI Content Specialist – Adoption

Engineering Manager

• You will own delivery, technical direction, and team health in the D&P service estate — the full learner and customer journey from diagnosis through prescription to onboarding and growth tracking.
• AI-heavy services (retrieval-augmented generation (RAG), LLM-scored assessment) that turn raw signal into a picture of where a learner or employer actually is.
• build the product which helps learners and customers understand the best learning course for their skills and career development, that leverages a customer's levy funds.
• turning a diagnosis into the right prescribed path and getting learners into it, where those decisions become visible to customers and learners.
• continuing to carve D&P logic out of the shared legacy monolith into dedicated services, while backing the newer AI-native product from beta toward scale.
• Hire well, give every report a real growth plan, and move the team into a high-performing, AI-native operating rhythm.
• Whiteboard distributed designs, review and negotiate the RabbitMQ event schemas and API contracts that ripple across services, and write production code yourself when it's the fastest way to de-risk or unblock.
• Use cycle time, change failure rate, and MTTR to balance shipping speed, debt, and change-safety on logic with genuine financial and regulatory blast radius.
• Prove better discovery-to-build-to-review loops on your own team and share what works across engineering.
• Work directly with Product and Design — and closely with go-to-market — to turn learner and customer behaviour into technical direction on the surfaces where eligibility and recommendation decisions become visible to real customers.

Senior Engineering Manager

Full-stack Engineer

• 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.
• Drive Engagement: Partner with AI Engineers to develop personalised learning experiences that adapt to individual pace, context, and need.
• Scale Systems: Operationalise AI-generated content at scale across our end-to-end messaging systems — defining the guardrails that ensure output feels relevant and human.
• Ship Code: Deliver high-quality architecture and write production code across our core stack: AWS, React, and TypeScript.

Senior Software Engineer, Growth

Financial Planning and Analysis

• Responsible for international entities — month end reporting and reconciliations and compliance
• Manage end-to-end intercompany accounting: recharges, loan balances, eliminations and intercompany agreement maintenance across the group
• Support transfer pricing compliance — maintaining intercompany pricing schedules, coordinating TP documentation with advisors and ensuring policies are accurately reflected in the ledger
• Own and evolve the group's financial controls and risk framework (RCM/SOX-lite): document key controls, perform regular testing, identify gaps and drive remediation
• Support audit and statutory compliance for international entities; act as first point of contact for auditor queries
• Support legal entity restructuring and group reorganisations, ensuring accounting and tax implications are captured
• Identify and implement process improvements in NetSuite to drive a rapid, efficient close cycle
• Produce analytical commentary on entity-level results for review by the Senior Finance Manager and CFO

Finance Manager

Artificial Intelligence

• You lead the team, own delivery, and write the production code that puts the product in front of real customers.
• You partner with the leadership to shape the vision and own how it comes to life.
• As a player-coach, you line-manage and grow a small core team while staying in the code, pulling in other engineers and specialists as the work needs them.
• You bring the product vision to life for real apprentices, customers and coaches.
• You own discovery, build, launch, and the calls on what to build next.

AI Build Lead

AI Engineer

• 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 — 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.

Staff AI Engineer – AI Transformation

• 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.

Senior AI Engineer – AI Transformation

• Own accounts payable and procurement end-to-end, including payment runs, supplier onboarding, account reconciliations, and correct VAT treatment on vendor invoices.
• Identify and deliver process improvements, using automation tools (e.g. Zapier, Google Apps Script) and AI tools (e.g. Claude, ChatGPT) to cut manual effort.
• Act as system owner for Ramp (Bill Payments and Expense Management) and Omnea (Procurement Orchestration).
• Contribute to M&A integration by onboarding acquired entities onto Multiverse’s finance infrastructure and standardising AP and procurement processes across international entities.
• Contribute to the design of internal controls using a risk-based approach.
• Manage multi-currency and cross-border payments in line with internal policy.
• Analyse transactional data to surface trends, inefficiencies, and improvement opportunities.
• Support month-end close through accurate data entry, accruals, reconciliations, and reporting inputs.
• Own the employee expense experience, reducing friction for employees to spend while building automated, AI-powered guardrails.
• Partner with stakeholders to resolve queries, drive adoption of best practices, and see improvement initiatives through from identification to delivery.