Senior AI Product Engineer

Elliptic·London, United Kingdomsenior

In short

→Diseñar y construir sistemas de inteligencia artificial autónomos para investigar delitos financieros en blockchains.
→Trabajar con LLMs, agentes, pipelines de recuperación y servicios backend en TypeScript/Node.js.
→Impacto directo: tu trabajo ayuda a detener el movimiento de dinero ilícito en redes blockchain.

Experiencia previa con productos de IA basados en LLMs en entornos de producción.

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What they ask for

✓Experiencia en ingeniería de software de 5-8 años.
✓1-2 años de experiencia en producción con características impulsadas por LLMs.
✓Capacidad para transformar problemas ambiguos en soluciones desplegables.
✓Habilidades sólidas en diseño de arquitectura para sistemas de IA escalables.
✓Capacidad de mentoría y liderazgo técnico.
✓Interés genuino en delitos financieros y blockchain.

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TypeScriptNode.jsLangChainLangGraphLLMsAgentic workflowsRetrieval pipelinesEvaluation frameworksAPIsEvent-driven systems

Who should you write to at Elliptic?

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Do you want to build the AI systems that compliance teams rely on to investigate real financial crime? Are you excited about taking agentic workflows from prototype to production at scale? Do you want your work to directly help catch bad actors moving money across blockchains? Elliptic is hiring a Senior AI Engineer to join our AI team. It is the team behind Elliptic's copilot, the AI product that helps compliance investigators trace fund flows, surface patterns, and respond to risk in real time. This role sits at the centre of that work, designing the agentic systems, LLM integrations, and backend services that turn complex blockchain data into useful answers. You'll join a focused team that cares about the quality of what it builds and gives you the space to do your best work. There's real ownership here, breadth across AI and backend systems, and the freedom to turn good ideas into shipped products. The problems are technically challenging, and the work is visible. The impact you will have: As a Senior AI Engineer on the AI team, you'll own significant parts of the Agentic stack that power Elliptic's copilot. You'll lead the design of agentic workflows, drive technical decisions on how we build and operate LLM-based features, and help raise the engineering standard across the team. You'll partner with product, web engineers, and your engineering lead to take complex problems from ambiguity to shipped product, and you'll mentor more junior engineers as the team grows. What you will do: Design and build agentic workflows and AI-powered features that power Elliptic's copilot, using LLM frameworks such as LangChain or LangGraph. Lead the design of agents, tool integrations, and retrieval pipelines that turn complex blockchain data into useful answers for investigators. Build and own evaluation frameworks that measure and improve the quality, reliability, and latency of LLM outputs. js. Drive technical design reviews and architecture decisions for AI workstreams. Mentor and coach more junior engineers through pair programming, code review, and design feedback. Raise the engineering bar across the team by promoting good practices in testing, observability, and AI system reliability. Influence cross-team decisions on how AI capabilities integrate with the rest of the Elliptic platform. What you will achieve in the first 6 months: Owned and shipped at least one significant AI capability end-to-end, from ambiguous problem statement through to production. Driven the technical direction of an AI workstream, including architecture, evaluation, and rollout. Established or improved at least one team practice for building AI systems (evals, observability patterns, prompt management, rollout safety). Mentored junior engineers on AI engineering practices and contributed to their growth. Built strong working relationships across product, web engineering, data engineering, and DevOps. Started to influence adjacent teams on how Elliptic builds with AI. You will be a great fit here if you: Care about building AI systems that work reliably in production, not just demos. Have strong instincts for trade-offs specific to LLM systems: cost vs latency vs quality, deterministic vs probabilistic behaviour, when to use an agent vs a workflow. Can take ambiguous AI problems and break them into shippable pieces with clear evaluation criteria. Communicate clearly with non-engineers (product, stakeholders, leadership) about AI capabilities and limitations. Have coached or mentored other engineers and enjoy raising the bar through reviews, pairing, and feedback. Are genuinely curious about the domain and find blockchain investigations and financial crime prevention interesting. Our ideal candidate has: 5-8+ years of software engineering experience, with at least 1-2 years of meaningful production work building LLM-powered features.

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