AI Product Engineer

Elliptic is building AI-powered tools that help compliance teams investigate crypto transactions faster and with greater confidence. Our Automation Forge team sits at the centre of that work, designing the AI systems and backend services behind Elliptic's copilot, the product that helps investigators trace fund flows, spot patterns, and respond to risk in real time. We're looking for an AI Engineer to help us design, build, and improve the LLM-powered features that make this possible. The impact you will have As an AI Engineer on the Automation Forge team, you'll build the agentic workflows, evaluation guardrails, retrieval pipelines, and supporting services that power Elliptic's copilot and other AI-driven features. You'll work with product managers, web engineers, and your engineering lead to turn complex blockchain data into intelligent, user-friendly experiences. Your work will help compliance teams trace fund flows, uncover patterns, and respond to risk faster and more confidently. Working collaboratively across disciplines, you’ll contribute to impactful features and continuously improve quality, reliability, and usefulness of our AI systems. Through this work, you’ll play an essential role in advancing Elliptic’s mission to make crypto markets safer, more transparent, and more efficient. What you will do: - Build and maintain AI-powered features and agentic workflows that power Elliptic's copilot, using LLM frameworks such as LangChain and LangGraph. - Design prompts, tool integrations, and retrieval pipelines that turn complex blockchain data into useful answers for investigators. - Develop and run evaluations to 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. - Collaborate with product, domain experts, web engineers, and your engineering lead to take features from prototype through to production. - Take part in technical design reviews, planning, and code reviews. - Care about how your services run in production: observability, cost, and reliability of LLM-based systems. What You'll Bring - 3 to 6 years of software engineering experience, with meaningful hands-on work building LLM-powered features in production. - Direct experience with LLM frameworks such as LangChain, LangGraph, LlamaIndex, or similar. - Practical understanding of prompt engineering, tool/function calling, subagents, structured outputs, and managing context windows. - Experience evaluating LLM outputs and iterating on prompts/pipelines, including building eval sets, measuring quality, and using observability tools (LangSmith, Langfuse, Arize, or similar). - 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. - Clear thinking about system design and trade-offs, especially the ones specific to LLM systems: cost vs latency vs quality, deterministic vs probabilistic behaviour. - Strong collaboration skills across engineering, product, and design. Nice to Have - Experience with agentic patterns: planning, multi-step reasoning, tool use loops. - Experience working with multiple model providers (Anthropic, OpenAI, open-weight models). - Hands-on Terraform, Kubernetes, or infrastructure-as-code experience. - Experience with observability platforms like Datadog (metrics, tracing, alerting). - Distributed or event-driven architectures (SNS, SQS, etc.). - Interest in cryptocurrency, blockchain, or compliance, though we're happy to bring you up to speed. Don't Meet Every Requirement? If this role excites you but your experience doesn't perfectly match every bullet point, we'd still love to hear from you. We value curiosity, willingness to learn, and diverse perspectives just as much as specific tool experience. Ensuring that people of all backgrounds, identities, and