Ph3About the Company /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. With more than 220 employees across Italy and the UK and backed by major partners such as Poste Italiane, Cabot Square Capital, United Ventures and Allianz, we are recognised as one of the most innovative fintechs headquartered in London. /p h3Role Overview /h3 pDesign, build and operate the shared AI/LLM platform and central backend services that enable Moneyfarm’s product teams to ship AI‑powered features across investing, pensions and share dealing. The platform must support guidance today toward fully personalised, regulated advice. /p h3Team Structure /h3 pThe AI team consists of five people. You will work directly with the AI Stream Lead, who owns prioritisation, cross‑team strategy and capacity allocation, while you are responsible for the technical design, implementation and operation of the AI stack. You will also set technical standards for the embedded engineers that ship AI features into the product teams. /p h3Environment /h3 pMoneyfarm’s backend is built on event‑driven microservices with Scala as the primary language. The AI services will be written in TypeScript and Python and must integrate with existing Scala services. Experience with functional programming, event‑driven patterns and asynchronous messaging is essential. /p h3Responsibilities /h3 ul liDesign and build the shared AI stack: LLM orchestration, retrieval, prompt management, evaluation, guardrails and observability /li liDevelop central backend services that power AI projects, written in TypeScript /li liEnsure production reliability, latency and cost optimisation for AI systems /li liDefine access and data governance patterns for LLM use (e.g., safe interaction with CRM or client data) /li liSet engineering standards and conduct technical reviews for embedded engineers shipping AI features in Bubbles /li liAdvise on tools, frameworks and vendors to support buy‑vs‑build decisions with the Stream Lead /li liPartner with Compliance on technical safety and evaluation patterns as we progress toward regulated advice /li liShort‑term deliverables include: standing up the production LLM platform, building core backend services, shipping the first wave of AI features, establishing evaluation and safety patterns under FCA/Consumer Duty, and setting review patterns for embedded developers /li /ul h3Requirements /h3 h3Must‑haves /h3 ul liShipped and operated LLM‑based features in production /li liStrong hands‑on backend engineering experience (write production services) /li liFluent in TypeScript (both front and backend) /li liFamiliarity with functional programming, ideally in Scala /li liDeep knowledge of software architecture design patterns /li liExperience designing or operating event‑driven architectures (Kafka, event sourcing, async messaging) /li liHands‑on experience with orchestration frameworks, retrieval‑augmented generation, evaluations and guardrails /li liClear thinking about identity, access and data governance, especially when LLMs interact with sensitive systems /li liPragmatic approach to cost/latency trade‑offs and model selection /li liComfortable being the technical voice in strategic conversations and providing constructive pushback /li liStrong grasp of the AI tooling landscape and ability to compare options quickly and credibly /li /ul h3Nice‑to-haves /h3 ul liExperience in regulated industries (financial services, healthcare, legal) /li liFamiliarity with Python /li liKnowledge of European data/privacy frameworks (GDPR, FCA expectations) /li liWorking knowledge of Scala for integration purposes /li liExperience across web and mobile full‑stack development /li liPrevious role in a small, high‑trust team where engineers shaped technical direction directly /li /ul h3Not a fit if /h3 ul liBackground is primarily ML research, model training or data science /li liSeeking an architect/lead role with delegated coding responsibilities /li liLooking for a fully greenfield environment without regulatory or legacy constraints /li liPrefers strict role boundaries – this team blends engineering and strategy /li /ul h3Logistics /h3 ul liFreelance / P.IVA contract arrangement /li /ul pCandidates who belong to ‘Categoria protetta’ (Legge 68/99) are more than welcome. /p /p #J-18808-Ljbffr