Staff AI Engineer

Multiverse

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’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’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’s first EdTech double unicorn. But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output. Join Multiverse and power our mission to equip the workforce to win in the AI era. THE ROLE 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. WHAT YOU WILL DO 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. WHAT WE ARE LOOKING FOR 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: * 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. * 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. * 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. * 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. * 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. * 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. 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. WHAT WOULD SET YOU APART * Experience in EdTech, regulated content, or domains where AI output quality has compliance or accreditation implications * Background as a founding engineer or technical co-founder * Published thinking or external contributions in AI engineering (talks, writing, open source) * Experience designing platform layers that other teams build on * Practical experience with MCP (Model Context Protocol) or equivalent agent integration standards WHAT WE ARE NOT LOOKING FOR * Pure ML research without production engineering experience. We need builders * 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 * 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 * 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 * Engineers who optimise for technical elegance over user outcomes. The architecture serves the product 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 - you'll 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 that’s always stocked! Our Commitment to Diversity, Equity and Inclusion We’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 & 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’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.

Baringa

ABOUT BARINGA  Baringa is a global consulting firm that partners with leaders to drive change and create value. With deep industry expertise, and enabled by advanced technology, the firm helps clients to deliver with greater confidence and certainty. With over 2,000 people across the UK, Europe, North America, Asia and Australia, the firm combines global insight with local understanding. The firm works across energy and resources, financial services, government and public sector, consumer products and retail, pharmaceuticals and life sciences, manufacturing, and technology, media and telecoms, with capabilities spanning strategy, transformation and operational excellence – all powered by advanced technology, data, AI and digital innovation. Clients value Baringa’s collaborative approach and the way its teams integrate seamlessly – all working with a shared understanding of what matters most. The firm is known for its kind, curious experts who listen closely and care deeply about client success as they help clients transform energy markets, modernise financial platforms, expand telecoms and digital networks through advanced data analytics, enable digital services in government, and unlock growth in consumer sectors. Certified as a Great Place to Work around the world, Baringa has been recognised by the Financial Times in 22 categories of its UK Leading Management Consultants rankings, and by Forbes for four consecutive years as one of the World’s Best Management Consulting Firms.   Our Solutions & AI Labs (SAIL) practice is looking for an experienced Senior Manager to lead consultancy engagements and grow our AI & Solutions Engineering capability. The Forward Deployed AI & Solutions Engineer role will lead the delivery of AI-enabled solutions embedded in our clients' teams, combining deep technical specialism with the commercial and leadership skills to grow and shape our practice.  This is a role for someone who thrives at the intersection of client advisory, technical architecture and hands-on delivery leadership – and who has a genuine passion for bringing AI solutions to production at scale.   Our Solutions & AI Labs (SAIL) practice focuses on helping clients control their data, turn it into actionable insights, and better leverage it through the use of AI and Machine Learning solutions directly embedded into business processes. We support clients across a number of industries and offer deep expertise in AI/ML, Cloud, Platform Engineering, and Managed Solutions.   What you will be doing  As a Senior Manager in SAIL, you will own and lead consultancy engagements end-to-end from shaping the opportunity and winning the work, through to delivery governance and team leadership. You will bring SME-level depth in at least one of AI/ML Engineering, Platform Engineering, or Software Engineering, and apply it to create real, lasting value for our clients.   Although we do not expect you to be an expert in all of the below activities simultaneously, our team consists of people who can work as advisors to our clients as well as bringing deep technical knowledge when needed. The profile of our typical engagements reflects that.   Key responsibilities span the following areas.   Engagement Leadership:  * Own and lead end-to-end delivery of complex AI and technology consulting engagements, taking accountability for scope, quality, risk and client outcomes.  * Lead and resource multi-disciplinary delivery teams including engineers, data scientists and consultants providing clear direction, technical oversight and people development.  * Manage engagement resourcing: forecast team requirements, work with practice leadership to staff engagements, and develop the talent pipeline through mentoring and support of junior practitioners.  * Proactively identify and manage delivery risks in complex stakeholder environments, escalating appropriately and maintaining client confidence throughout.  * Communicate clearly to both technical teams and senior client stakeholders, translating complexity into actionable insight and decisive recommendation.  * Conduct rigorous technical reviews and uphold engineering and delivery standards across every engagement you lead.   Business Development & Bid Support:  * Play a leading role in business development: identifying new opportunities, shaping propositions, and supporting or leading bids and tender responses for AI and technology engagements.  * Contribute to proposal writing, articulating Baringa’s capabilities and differentiators, including authoring technical and delivery sections of bid responses to client tenders and RFPs.  * Build and maintain strong client relationships, acting as a trusted advisor and developing opportunities for follow-on engagement.  * Support practice-level growth initiatives, including account planning, capability development, and go-to-market positioning for AI and solutions engineering services.   Technical Architecture & Delivery:  * Lead architecture design for AI-enabled platforms and cloud solutions, balancing technical excellence with delivery pragmatism and commercial realities.  * Provide hands-on technical direction where required – reviewing designs, code and delivery artefacts to maintain quality standards across the engagement.  * Champion the path from prototype to production: driving robust, scalable and secure AI deployments that go beyond proof-of-concept thinking to real business impact at scale.  * Act as a credible technical voice with client architects, CTOs and engineering leads, earning trust through depth of knowledge and a demonstrable delivery track record.  AI/ML Specialism  You will bring expert-level knowledge in at least one of the following domains, and working knowledge across the others:   Agentic AI & LLM Engineering:  * Design and build production-grade agentic systems using major LLM SDKs and agent frameworks; deep knowledge of RAG, MCP servers and prompt engineering at scale.  * Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities and AI product stacks.   Machine Learning Engineering:  * End-to-end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection.  * Practical knowledge of ML frameworks (e.g. scikit-learn, PyTorch, XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI).  Platform & Cloud Engineering:  * Architecture and delivery of scalable cloud data and AI platforms on AWS, Azure or GCP; experienced with containerisation, IaC, event-driven architectures and CI/CD.  * Track record of delivering production Python services and APIs; working knowledge of cloud-native application patterns and release practices.   Software Engineering:  * Production-grade Python services (FastAPI, AWS Lambda, event-driven patterns) and front-end development with React/Next.js, Material UI and SWR.  * Cloud architecture design capability across major providers; rounded understanding of database trade-offs – relational, NoSQL, graph and caching strategies.  * Strong engineering practices: CI/CD, testing (Jest, Cypress, React Test Library), release management and security-conscious development.   * A genuine passion for AI solutions and specifically for the complexity of delivering them to production at scale. You should be as energised by the hard problems of operationalisation, reliability and governance as by the technology itself.   Your Skills and Experience   We're seeking a technically credible, commercially aware leader who brings a rare combination of delivery accountability, client advisory skill, and deep AI/technology specialism. You will be someone energised by the complexity of taking AI solutions to production at scale – and who can inspire a team and a client with that same passion.  * 7+ years in technology consulting, software engineering or AI/ML, with at least 3 years in a senior leadership role – including direct accountability for end-to-end engagement delivery, resourcing and commercial outcomes.  * Experience supporting or leading bid and proposal activity, including writing technical and delivery sections of responses to client tenders and RFPs.  * SME-level depth in at least one of: Agentic AI/LLM Engineering, Machine Learning Engineering, Platform & Cloud Engineering, or Software Engineering – with strong architecture and design capability across cloud, data and AI domains.  * Proven ability to build and lead high-performing delivery teams in complex stakeholder environments, with experience engaging comfortably at CTO or engineering director level.  * Clear, confident communicator – able to make the complex accessible for technical and non-technical audiences alike, and to represent Baringa’s expertise with credibility.  * Master’s degree in Computer Science, Engineering, Mathematics, Data Science or related discipline, or equivalent depth through relevant professional certifications (e.g. AWS Solutions Architect Professional, Google Professional ML Engineer).  * Desirable: prior experience as a forward-deployed or embedded engineer within a client environment; exposure to regulated industries such as energy, financial services or public sector.  If you are excited by the opportunity to lead meaningful AI and technology engagements for major clients and thrive in a collaborative, people-first culture that values both technical rigour and human connection we would love to hear from you.  JOIN US All applications received will be reviewed by a member of our Talent Acquisition team. We never rely solely on automated screening or AI tools to make hiring decisions. Your application will be considered for employment without regard to race, ethnicity, religion, gender, gender identity or expression, sexual orientation, nationality, disability, age, faith or social background. We do not filter applications by university background and encourage those who have taken alternative educational and career paths to apply. We would like to actively encourage applications from those who identify with less represented and minority groups. We operate an inclusive recruitment process, ensuring reasonable adjustments where needed. Please contact a member of our Recruitment Team to discuss further.   BARINGA PRIVACY NOTICES For UK & EU Your personal data will be retained by Baringa for up to two years, in accordance with our UK Recruitment Privacy Notice / EU Recruitment Privacy Notice, to evaluate your application and meet our legal and reporting obligations. In line with the General Data Protection Regulation (GDPR), you have the right to request access to, rectification, or erasure (subject to legal limitations) of your personal data. For more information, please contact us at privacy@baringa.com For the USA Your personal data may be retained by Baringa for up to two years, as outlined in our Recruitment Privacy Notice (AMER & APAC), to support the recruitment process and internal reporting requirements. Where applicable, and in accordance with relevant federal and state laws, you may have the right to request access to or correction of your personal information. For further details, please contact privacy@baringa.com For Australia & Singapore Your personal data will be retained by Baringa for up to two years, in accordance with our Recruitment Privacy Notice (AMER & APAC), to assess your application and meet applicable reporting and legal obligations. In line with the Australian Privacy Act and Singapore’s Personal Data Protection Act (PDPA), you may have rights to access, correct, or request limited deletion of your personal data. For more information, please contact us at privacy@baringa.com

ClearScore

Senior Knowledge Manager Knowledge is becoming a source of competitive advantage. Organisations that have organised, current and trusted knowledge, usable by both people and AI, will make better decisions, move faster, and serve customers better than those that do not. We want our knowledge to be a quiet advantage for ClearScore Group, not a tax. This role exists to do two things at once. The first is hands-on. We have an ever-growing set of working documents, Notion pages, dashboards, and content across a cloud drive, SharePoint and Slack. Some of it should no longer exist. Some of it is foundational and is at risk of being lost. Someone needs to roll their sleeves up: write, rewrite, restructure, decommission, and own the canonical index of what we actually know. This is part librarian, part documentarian, part data steward. The second is strategic. We need to stop treating our corpus of working documents as if it were authoritative knowledge, build a deliberate corpus that is, maintain it actively as facts change, fill the gaps in critical domains like products, regulation and markets, and make sure every piece of significant work leaves behind reusable learning. This is the knowledge architect side of the role. The person in this seat owns the standards, owns the canonical index, does the work where it has to be done by them, and gets the rest done through a federated network of domain owners and maintainers across the Group. This is a mid-level individual contributor role with no direct reports. It sits centrally and reports to the VP of Operations who reports directly to the CEO. The reporting line is deliberately function-agnostic: not inside Data, not inside Architecture, and not inside AI Engineering. This is so the role can set standards across all of those functions without being captured by any of them.   What you will be doing: 1. Produce a roll out a written Knowledge Strategy: Endorsed by the executive, this should explicitly address how we do knowledge management in an AI-enabled world. 2. Separate knowledge from working documents: Define what counts as knowledge for the Group (content that is authoritative, owned, current and worth trusting) versus working documentation such as drafts, scratchpads, meeting notes and in-flight thinking, set a higher bar for publishing to the knowledge corpus and use LLM-based tools to help enforce it. 3. Actively maintain the corpus: Set review cycles, ownership and freshness expectations across the corpus and run the rhythm that keeps them honest, surface and resolve stale, duplicate or contradictory content (using LLM-based tools to scan for out-of-date facts, flag contradictions and identify duplicates across thousands of pages), treat decommissioning as a first-class activity with a credible first pass at the existing estate inside six months, maintain clear lineage, and work with Legal, Risk and Compliance on access, retention and regulator-facing obligations across our markets. 4. Fill the gaps in critical domains: Map the domains across the Group, identify where authoritative knowledge is thin or missing, and work down a prioritised backlog through a federated maintainer model where each significant domain has a named expert and a named maintainer working to a standard you set and a cadence you run, sitting alongside teams during the moments that generate important knowledge such as launches, incidents, regulatory responses and M&A so the output is captured at the time, not retrofitted later. 5. Make compounding learning a habit: Establish a simple, mandatory pattern for every significant piece of work to leave behind structured learning (what was the question, what did we decide, what happened, what would we do differently), make that the default output of quarterly business reviews, retros, incident washups, experiments and major decisions rather than a separate task that gets dropped, and curate the resulting record so it is actually retrievable later by people and by AI tools. 6. Equip our knowledge for AI consumption: Be the person who understands, in practical terms, how modern AI systems consume organisational knowledge (retrieval, structure, metadata, permissions) and who specifies what good looks like from the knowledge side, working with the AI Lead, Chief Architect, Chief Data Officer and Engineering on how knowledge is indexed, retrieved and served into internal AI tools (you own the content and its structure; they own the systems that consume it). You are not expected to build production retrieval systems yourself, but to know enough to make sensible design decisions, write the requirements, and spot when an AI answer is grounded in the wrong source. 7. Roll your sleeves up: Author and maintain the Group's canonical knowledge index: the single place any employee or internal AI tool goes to find the authoritative source on a topic.   Skills we'd love you to have This role suits someone who brings order to complexity, is comfortable operating across functions without formal authority, and prefers doing the work to talking about it. The technical depth below can be grown into; the judgement and bias to action cannot. ESSENTIAL * Track record of materially improving how knowledge is organised, owned and maintained in a mid-to-large organisation, through a mix of strategy, standards and personally doing the work. * Strong writer and structurer. Able to turn messy source material into clear, accurate, well-structured content; able to design a taxonomy and an index that other people can actually use. * Comfortable with data governance concepts as applied to knowledge: ownership, custodianship, classification, access, lineage, retention. Aware of the obligations that come with operating in regulated markets. * Practical understanding of how modern AI tools consume organisational knowledge, including retrieval, structure, metadata, and permissions, enough to specify requirements clearly to Data, Engineering and the AI Lead, and to evaluate whether an AI answer is grounded in the right source. Not expected to be an ML engineer. * Fluent across the tooling landscape we use or might use: wikis, documentation systems, knowledge bases, document stores, search. * Able to influence without authority. Able to say no, hold a standard, run a federated network of maintainers, and stay constructive through it. * Bias to action. Happy to write the first version, fix the broken link, rename the file, restructure the folder, archive the page that nobody has opened in two years. DESIRABLE * Experience in financial services, fintech, or another regulated industry with meaningful documentation and records obligations. * Background that includes library or information science, technical writing, knowledge engineering, records management, or data governance. * Experience operating a federated model, with appointed experts and maintainers across functions, rather than relying on a central team. * Exposure to API-led businesses where knowledge is exposed to external systems as well as internal staff. * Direct experience of organisations going through the transition to AI-assisted retrieval, on the knowledge side rather than the platform side. Why ClearScore? ClearScore is the UK's #1 credit score and report app. We are also present in South Africa, Australia and Canada, with more than 20 million users globally and growing fast. Someone joins ClearScore every 20 seconds. We have established relationships with over 50 of the main lenders in the U.K., and have been a trusted tool for customers to manage their credit and make better financial decisions. Since October 2016 we have helped 1.8 million users take out a new credit card or loan. We are user-centric at our core and we believe in leveraging technology to enable positive financial choices. We are design-led and data-driven and we embed these behaviours in everything we do. Our company culture is a fundamental part of all we have achieved. We believe in hiring smart, driven, passionate and diverse people who are keen on having a real impact in our organisation. We trust you to manage your own time so we offer flexible work and no fixed desk hours. We don't micromanage and we believe in measuring outcomes rather than effort. We have an inclusive culture where all, regardless of seniority, are encouraged to contribute with their ideas, look after their wellbeing and actively seek opportunities for career growth. If you feel like this could be the place for you, apply and our Talent team will be happy to share more. Benefits: * 25 paid holidays and a “duvet day” on your birthday * Hybrid Work Environment * Private health and dental cover - including mental health support through Bupa  * GP office visits * Life assurance scheme * Up to 6% matched pension * Regular Lunch and Learns with guest speakers * Dog-friendly office * Daily breakfast and free snacks * Access to discounts via Cobens Extras  * Free sports and social clubs * Continued investment into learning and development  * Leadership-led training * In-house psychotherapist * Financial coach to help you plan and achieve your goals * No clock-watching culture * Generous maternity and paternity plans * Culture and inclusion representatives * Transparent pay structure and a career growth plan   Equal Opportunities ClearScore is committed to providing equal employment opportunities to all qualified individuals. As an equal opportunity employer, we are able to make reasonable adjustments to accommodate individuals with disabilities during the recruitment and selection process. If you require accommodation, please inform us in advance, and we will work with you to meet your needs. Our Hybrid Model   We embrace a dynamic hybrid work environment that balances flexibility with collaborative in-person experiences. Our approach is designed to foster innovation, team connection, and individual productivity. * Levels 1-5: Minimum 2 days per week in-office * Level 6 and above: Minimum 3 days per week in-office We believe this structure offers the best of both worlds - the flexibility of remote work and the synergy of face-to-face collaboration. Our office days are carefully coordinated to maximise team interactions and learning/ mentorship opportunities. What This Means for You: * Flexibility to manage your work and life * Dedicated in-office days for team building and collaborative projects *  Office facilities (with plants!) designed for productive interactions * Clear expectations and support for maintaining our hybrid schedule We’re committed to creating an inclusive environment that accommodates diverse needs while maintaining our collaborative culture. Join us in shaping the future of work! Note: While we offer flexibility, commitment to our hybrid schedule is an important aspect of our team culture and performance expectations.     Inclusion Policy We are always looking for talented individuals to join ClearScore. We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for our people. Please see our People Policy Notice at https://www.clearscore.com/people-notice.