Ph3Who We Are /h3 pWe are a rapidly growing pan-European digital wealth manager, serving over 167,000 active investors with more than £5.5 billion invested on our platform. We began in Milan in 2011 with the purpose to help more people improve their financial well‑being by making personal investing simple and accessible through technology. Fast forward to today, and we are recognised as one of the most innovative fintechs, headquartered in the heart of London. With a team of 220+ people across 4 offices in Italy and the UK, we are proudly backed and funded by major partners including Poste Italiane, Cabot Square Capital, United Ventures, and Allianz. /p h3Our Vision /h3 pOur vision is to combine passion, expertise, and technology to provide best‑in‑class investment solutions and advice that protects and grows client wealth over time. /p h3Our Core Values /h3 ul liRelationships are our first asset: We’re one team built on trust, honesty, and transparency. We value our relationships above all else. /li liTrust drives success: We give each other the space to grow. We empower our employees to succeed, so they can make a real impact. /li liOur customers dream big, just like us: We see the bigger picture and we make sure our customers see it, too. We’re always focused on the best outcomes for our clients and for each other, no matter what the goal or how big the dream. /li /ul h3What this means in practice /h3 pAt Moneyfarm, our success comes from the impact each of us makes. We move with purpose, urgency, and ambition, focused on delivering outcomes that matter for our clients and our business. Everyone is empowered to take ownership, challenge the status‑quo, and turn bold ideas into results. As we evolve, we embrace AI as a catalyst for sharper thinking, smarter decisions, and even greater impact. Our diversity makes this possible. Different perspectives, backgrounds, and experiences fuel our creativity and drive better decisions — it’s our competitive edge. We value people for who they are and their unique strengths: that’s why we offer flexible ways of working to support them in doing their best work. /p bCandidates who belong to ‘Categoria protetta’ (Legge 68/99) are more than welcome! /b h3The Role in One Line /h3 pDesign, build, and operate the shared AI/LLM platform and the central backend services behind it so Moneyfarm’s product teams can ship AI‑powered features across investing, pensions, and share dealing, from guidance today toward fully personalised, regulated advice. /p h3How The Team Works /h3 pThe AI team is small (five people) and tightly coupled. You’ll work alongside the AI Stream Lead as the senior engineering counterpart on the team. The Stream Lead owns prioritisation, cross‑team strategy, capacity allocation, and final buy‑vs‑build calls. You own how the AI stack is actually built and operated, and you’re the technical voice in those strategic decisions. Many things will be co‑decided in practice — strategy and engineering are tightly coupled here, and we want it that way. This is a hands‑on role. As well as designing the platform, you’ll write the central backend services that power our AI projects — APIs, data access layers, integration points between LLMs and our internal systems. We’re not hiring an architect who delegates the build. Three embedded engineers ship AI features inside the product teams (we call them “bubbles” and include tech, product, marketing and all other functions required to run that vertical). You set the technical standards they work to and review their work; the Stream Lead allocates their capacity. /p h3Our Environment /h3 pMoneyfarm’s backend runs on event‑driven microservices, with Scala as a primary language across much of the platform. The AI team’s own services will be built in TypeScript and Python, but you’ll integrate with — and sometimes touch — Scala services. Comfort with functional programming and event‑driven patterns is part of working effectively here. /p h3Responsibilities /h3 ul liThe shared AI stack: LLM orchestration, retrieval, prompt management, evaluation, guardrails, observability /li liCentral backend services that drive AI projects — building them yourself, in TypeScript /li liProduction reliability, latency, and cost of AI systems running in the firm /li liAccess and data governance patterns for LLM use (e.g., how an LLM safely accesses CRM or client data) /li liEngineering standards and technical review for embedded engineers shipping AI features in bubbles /li liTechnical recommendations on tools, frameworks, and vendors — feeding into buy‑vs‑build decisions made with the Stream Lead /li liPartnering with Compliance on technical safety and evaluation patterns as scope progresses toward regulated advice /li liWhat you’ll work on in the first 6‑12 months /li liStanding up the production LLM platform Moneyfarm’s product teams will build on /li liBuilding the central backend services that the platform and bubble integrations depend on /li liShipping the first wave of AI features across investment guidance and onboarding /li liEstablishing evaluation and safety patterns that hold up under FCA/Consumer Duty scrutiny /li liSetting the engineering bar and review patterns for embedded developers as they come online /li /ul h3Requirements /h3 bMust‑haves /b ul liShipped and operated LLM‑based features in production /li liStrong hands‑on backend engineering — you’ll write production services, not just design them /li liFluent in TypeScript (both, not either) /li liFamiliarity with functional programming — ideally in Scala /li liStrong knowledge of software architecture design patterns /li liExperience designing or operating event‑driven architectures (Kafka, event sourcing, async messaging patterns) /li liHands‑on with orchestration frameworks, RAG, evals, and guardrails /li liThinks clearly about identity, access, and data governance — especially when LLMs touch sensitive systems /li liPragmatic on cost/latency trade‑offs and model selection /li liComfortable being the technical voice in strategic conversations and pushing back when needed /li liFluent in the AI tooling landscape — can compare options quickly and credibly /li /ul bNice‑to‑haves /b ul liExperience in regulated industries (financial services, healthcare, legal) /li liFamiliarity with Python /li liFamiliarity with European data/privacy frameworks (GDPR, FCA expectations) /li liWorking knowledge of Scala specifically (you’ll integrate with our Scala services) /li liMobile or full‑stack range (the broader product is web + mobile) /li liPrevious role in a small, high‑trust team where the engineer shaped technical direction directly /li /ul bNot a fit if /b ul liBackground is primarily ML research, model training, or data science /li liLooking for an architect/lead role where someone else writes the code /li liWants a fully greenfield environment with no regulatory or legacy constraints /li liPrefers strict role boundaries — this is a small team where engineering and strategy overlap by design /li /ul bLogistics /b ul liPermanent employee, Italy contract /li liHybrid role: minimum 2 times a week in the office /li /ul /p #J-18808-Ljbffr