Elliptic is a digital asset data and intelligence firm that tracks and labels blockchain assets and entities to provide crypto compliance and analytics.
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. - Design and build the backend services, APIs, and event-driven systems that support these features, using TypeScript and Node.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. - Direct experience with LLM frameworks such as LangChain, LangGraph, or similar. - Hands-on experience building agentic systems: tool use, multi-step reasoning, planning, memory, and human-in-the-loop patterns. - Practical understanding of prompt engineering, structured outputs, context management, and managing the trade-offs of working with LLMs. - Experience building and running evaluations for LLM outputs (eval sets, LLM-as-judge, regression testing). - Strong backend skills in TypeScript / Node.js, with solid API design. - Cloud experience (AWS: Lambda, ECS, S3, or similar). - Database proficiency across SQL (Postgres) and some NoSQL exposure. - Demonstrated ability to mentor and coach other engineers. - Uses AI coding assistants (Copilot, Cursor, Claude, etc.) critically and effectively as part of their day-to-day workflow. Bonus points for: - Experience with retrieval-augmented generation (RAG) and vector databases (pgvector, Pinecone, or similar). - Experience designing multi-agent systems and agent orchestration patterns. - Familiarity with LLM observability tools (LangSmith, Langfuse, Arize, or similar). - Experience working with multiple model providers (Anthropic, OpenAI, open-weight models) or with fine-tuning. - Hands-on experience with Terraform, Kubernetes, or infrastructure-as-code tooling. - Experience with observability platforms like Datadog. - Distributed or event-driven architectures (SNS, SQS). - Interest in cryptocurrency, blockchain, or compliance. JOB BENEFITS > How we work: - Hybrid working and the option to work from almost anywhere for up to 90 days per year - £500 Remote working budget to set up your home office space > Learning & Development: - $1,000 Learning & Development budget to use on anything (agreed with your manager) that contributes to your growth and development > Vacation/