Founding Engineer (Platform)

9fin

About 9fin 9fin is the AI platform powering global debt markets — the world’s largest asset class at over $145 trillion. Debt markets are vast, global, and mission-critical, yet still run on fragmented data, PDFs, and manual workflows. 9fin replaces this broken infrastructure with a single platform that centralises proprietary credit data, deep analysis, and high-value workflows across global markets. Today, 9fin powers teams at 300+ blue-chip institutions worldwide, including global banks, asset managers, private equity firms, law firms, and advisors. The business is scaling at exceptional speed, with rapid expansion in the US and best-in-class retention driven by deep workflow adoption. We’re at a defining inflection point. With proven product-market fit and strong, global market pull, 9fin is accelerating toward becoming the category-defining platform for debt markets worldwide. We’re looking for a Staff Engineer to lead the technical vision and architecture for 9fin’s New Markets engineering organisation. In this role, you’ll define and evolve the system design that underpins our future expansion—owning the end-to-end architecture, setting technical direction, and ensuring our platforms scale effectively as we enter new markets. You’ll create clear technical documentation, align multiple engineering teams around a shared vision, and guide execution by helping teams make thoughtful trade-offs. This is a high-impact, hands-on leadership role on the IC track. You’ll operate across strategy and execution—partnering with 6+ teams, contributing directly to critical code paths when needed, and raising the engineering bar across the organisation. WHAT YOU’LL DO * Partner with other staff engineers to propose high impact engineering proposals . * You will influence technical strategy, participate in technical governance and decision making . You align the technical vision with various stakeholders (primarily the engineering leadership layer) . * Design and scale backend services, APIs, and data platforms powering 9fin’s new market products * Work on complex entity mapping and data modelling challenges across new market’s data sources * Drive database decoupling and system modularisation to improve scalability, flexibility, and long-term maintainability * You will review and guide architecture across teams, helping avoid unnecessary coupling and complexity while keeping teams focused on pragmatic, high-impact solutions. * Dive into complex legacy systems, identify root causes of friction, and define a clear path to modernisation * Deliver high-quality, reliable production code through testing, logging, and alerting * Move between deep debugging and high-level system design to shape our platform evolution * Set a high bar for engineering through hands-on coding and strong technical leadership. * Leverage AI-assisted engineering to accelerate system understanding and delivery * Establish best practices, guardrails, and tooling to improve engineering velocity and safety * Ensure systems are scalable, reliable, and adaptable as we grow * Partner closely with Engineering and Platform * You will raise our technical bar by mentoring senior engineers, improving IC hiring and levelling practices, and helping shape how we develop technical talent across 9fin WHAT WE’RE LOOKING FOR * Proven track record of building and delivering backend systems from development to production, especially in data intensive environments * Deep expertise in distributed systems, APIs, and data pipelines * Strong experience with data modelling, entity resolution/mapping, and complex relational domains * Familiarity with event-driven architectures, Kubernetes, and cloud-based infrastructure like AWS * Experience in database decoupling, service-oriented architectures, or platform modularisation * Proficiency in Python (or similar backend languages) * Experience modernising legacy systems and improving platform architecture * Proven ability to lead complex technical initiatives end-to-end * Strong product and customer mindset * Comfortable operating in ambiguity and driving clarity * Skilled at balancing hands-on technical work with guiding and aligning others * Communicate clearly and effectively with technical and non-technical audiences. Nice to have: * Experience as a founding engineer or CTO at a startup, or building systems from scratch in early-stage environments Benefits We’re a scaling start up and we enjoy sharing our success, when the company succeeds, we always reinvest that in our people. We also offer huge amounts of responsibility, an abundance of opportunity for growth and a platform to truly excel. Financial & Insurance * Competitive Salary (our salary bands are benchmarked at the top end of the market) * Equity options * Pension (your minimum contributions are 4% with 9fin matching up to 7%) * Private Medical Insurance * Paid sick leave with Income Protection for long periods of illness * Group Life Assurance * Season Ticket Loan & Cycle to Work schemes Time off * 25 holiday days per year * Local public holidays (with the ability to exchange them for alternative days) * Hybrid working model, to allow you the flexibility to decide how, where and when you do your best work * Work abroad for up to 3 months a year * 1 month paid sabbatical after 5 years of service * Enhanced parental leave & flexible working arrangements available Training & Culture * Professional learning and development budget * Quarterly team socials * Summer and Winter company social events 9fin is an equal opportunities employer At 9fin we are dedicated to building and promoting a fair and inclusive workplace where everyone can reach their full potential and truly belong. We recognize that building diverse teams enables a more creative and productive environment. If you’re excited about this role but your experience doesn’t perfectly align with the job description, we encourage you to apply anyway. You might just be who we’re looking for — either for this role, or perhaps another.

9fin

About 9fin 9fin is the AI platform powering global debt markets — the world’s largest asset class at over $145 trillion. Debt markets are vast, global, and mission-critical, yet still run on fragmented data, PDFs, and manual workflows. 9fin replaces this broken infrastructure with a single platform that centralises proprietary credit data, deep analysis, and high-value workflows across global markets. Today, 9fin powers teams at 300+ blue-chip institutions worldwide, including global banks, asset managers, private equity firms, law firms, and advisors. The business is scaling at exceptional speed, with rapid expansion in the US and best-in-class retention driven by deep workflow adoption. We’re at a defining inflection point. With proven product-market fit and strong, global market pull, 9fin is accelerating toward becoming the category-defining platform for debt markets worldwide. WE'RE LOOKING FOR A PRINCIPAL ENGINEER TO OWN THE HARDEST TECHNICAL PROBLEMS AT 9FIN — THE ONES THAT CUT ACROSS TEAMS, DON'T BELONG CLEANLY TO ANY SINGLE DOMAIN, AND HAVE THE HIGHEST CONSEQUENCE IF THEY GO WRONG. 9fin sits at the intersection of financial data and AI. We ingest, model, and surface complex debt capital markets intelligence at scale. What we need now is someone who works across all of our areas (from AI, to Analytics, Platform, and Product Engineering) — setting the architectural standard, owning the foundational problems nobody else owns, and being the senior technical voice that makes the whole thing cohere. This is not a domain lead role. It's not advisory either. It's for someone who is energised by complexity and ambiguity, who wants to own the problems that are genuinely hard, and who can move between deep technical work and cross-org influence without losing credibility in either direction. WHAT YOU'LL OWN These are the cross-cutting problems that don't belong cleanly to any one team — but that everything else depends on. Core data model and entity resolution 9fin's value depends on how well we understand financial entities and the relationships between them — issuers, instruments, deals, counterparties, legal documents. This is hard: data is messy, sources conflict, and the model has to serve analytics, AI, and product simultaneously. You'll own the decisions that shape this foundation and hold the standard for how we model and resolve financial data at scale. Foundational architectural decisions When a decision is big enough to affect multiple teams and long-lived enough to be hard to undo, it lands with you. You'll write the RFCs, facilitate the debate, make the call, and be accountable for the outcome. WHAT YOU'LL OVERSEE You'll work closely with the Heads/Directors of Analytics, AI, Platform, and Product Engineering — not to run their domains, but to raise the bar across all of them. * Bring architectural coherence to decisions made within individual domains * Identify technical risks and compounding complexity before they become incidents * Set standards for engineering quality — system design, observability, reliability, API design — that every team builds to * Be the senior technical voice in cross-team planning, roadmap discussions, and major build vs. buy decisions * Mentor and stretch the most senior engineers across the org WHAT WE'RE LOOKING FOR You're the person who: * Has operated at principal or staff level in a data-intensive, fast-moving engineering org — and has the range to show for it * Can credibly walk into a conversation about data pipeline architecture, RAG evaluation, API design, or system scalability — and add something useful in all of them * Owns problems, not just opinions. You're not here to review and advise; you're here to make calls and be accountable for them * Writes code when it matters — the proof of concept that validates a direction, the deep dive that unblocks the team, the PR that sets the standard others build from * Has strong opinions about what good engineering looks like and can defend them without being precious about being wrong * Is energised by the problems nobody else can solve, not unsettled by them Technical bar: * Deep experience with complex data modelling, entity resolution, and data pipelines in production environments * Proven experience designing and shipping AI/LLM systems — RAG, structured extraction, evaluation frameworks — beyond the prototype stage * Strong backend and distributed systems knowledge: APIs, service architecture, scalability, observability * Experience making and owning foundational architectural decisions that affected how an entire engineering org worked * Proficiency in Python; comfort across the stack where it matters Nice to have: * Experience with financial data, legal documents, or other semi-structured, domain-rich datasets * Background as a founding engineer, early-stage CTO, or technical lead who has built systems from scratch and lived with the consequences WHY THIS ROLE * The problems you'll own are genuinely hard — messy financial data, complex entity relationships, AI systems where correctness really matters * You'll have real authority over foundational decisions, not just influence over them * 9fin's engineering org is strong and growing — you'll be working with and stretching great engineers, not compensating for weak ones * High ownership, high impact, and the chance to shape how a serious data and AI company scales its technical foundations Benefits We’re a scaling start up and we enjoy sharing our success, when the company succeeds, we always reinvest that in our people. We also offer huge amounts of responsibility, an abundance of opportunity for growth and a platform to truly excel. Financial & Insurance * Competitive Salary (our salary bands are benchmarked at the top end of the market) * Equity options * Pension (your minimum contributions are 4% with 9fin matching up to 7%) * Private Medical Insurance * Paid sick leave with Income Protection for long periods of illness * Group Life Assurance * Season Ticket Loan & Cycle to Work schemes Time off * 25 holiday days per year * Local public holidays (with the ability to exchange them for alternative days) * Hybrid working model, to allow you the flexibility to decide how, where and when you do your best work * Work abroad for up to 3 months a year * 1 month paid sabbatical after 5 years of service * Enhanced parental leave & flexible working arrangements available Training & Culture * Professional learning and development budget * Quarterly team socials * Summer and Winter company social events 9fin is an equal opportunities employer At 9fin we are dedicated to building and promoting a fair and inclusive workplace where everyone can reach their full potential and truly belong. We recognize that building diverse teams enables a more creative and productive environment. If you’re excited about this role but your experience doesn’t perfectly align with the job description, we encourage you to apply anyway. You might just be who we’re looking for — either for this role, or perhaps another.

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.