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Elliptic is seeking a Senior AI Product Engineer to join its AI team, which builds the agentic systems powering Elliptic's copilot—an AI product that helps compliance investigators trace fund flows, surface patterns, and respond to financial crime risk in real time.
In this role, you will own significant portions of the agentic stack that powers the copilot. You'll design and build agentic workflows and AI-powered features using LLM frameworks like LangChain or LangGraph. You'll lead the design of agents, tool integrations, and retrieval pipelines that transform complex blockchain data into actionable answers for investigators. You'll build and own evaluation frameworks that measure and improve the quality, reliability, and latency of LLM outputs.
You'll also design and build backend services, APIs, and event-driven systems supporting these features using TypeScript and Node.js. You'll drive technical design reviews and architecture decisions for AI workstreams, mentor junior engineers through pair programming and code review, and raise the engineering bar across the team by promoting best practices in testing, observability, and AI system reliability. You'll influence cross-team decisions on how AI capabilities integrate with the broader Elliptic platform.
In your first six months, you'll own and ship at least one significant AI capability end-to-end, drive the technical direction of an AI workstream, establish or improve team practices for building AI systems, mentor junior engineers, build strong cross-functional relationships, and begin influencing adjacent teams on AI development.
You'll work in a focused team that values quality and gives you space to do your best work. There's real ownership, breadth across AI and backend systems, and freedom to turn good ideas into shipped products. The problems are technically challenging and the work is visible.
The role is hybrid with the option to work from almost anywhere for up to 90 days per year.
REQUIREMENTS:
- 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 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 day-to-day workflow
BONUS:
- 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
