Senior AI Product Engineer
Build and operate production agentic AI systems for Elliptic’s compliance copilot, including LLM workflows, evaluations, retrieval, APIs, and backend services. The role requires senior software engineering experience, production LLM expertise, strong TypeScript/Node.js skills, and experience mentoring engineers.
About the job
Responsibilities
- Design and build agentic workflows and AI-powered features for 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 to measure and improve LLM output quality, reliability, and latency.
- Design and build backend services, APIs, and event-driven systems using TypeScript and Node.js.
- Drive technical design reviews and architecture decisions for AI workstreams.
- Mentor and coach junior engineers through pair programming, code review, and design feedback.
- Promote testing, observability, and AI system reliability practices.
- Influence cross-team decisions about integrating AI capabilities into the Elliptic platform.
First Six Months
- Ship at least one significant AI capability end-to-end, from problem definition through production.
- Drive the technical direction of an AI workstream, including architecture, evaluation, and rollout.
- Establish or improve a team practice such as evaluations, observability, prompt management, or rollout safety.
- Mentor junior engineers and contribute to their growth.
- Build relationships across product, web engineering, data engineering, and DevOps.
- Influence adjacent teams’ approach to building with AI.
Requirements
- 5–8+ years of software engineering experience, including 1–2 years of meaningful production work building LLM-powered features.
- Experience with LLM frameworks such as LangChain, LangGraph, or similar.
- Hands-on experience building agentic systems, including tool use, multi-step reasoning, planning, memory, and human-in-the-loop patterns.
- Practical understanding of prompt engineering, structured outputs, context management, and LLM trade-offs.
- Experience building and running LLM evaluations, including evaluation sets, LLM-as-judge, and regression testing.
- Strong backend skills in TypeScript and Node.js, with solid API design experience.
- Cloud experience with AWS, including Lambda, ECS, S3, or similar services.
- Database proficiency with SQL and Postgres, plus some NoSQL exposure.
- Experience mentoring and coaching engineers.
- Effective use of AI coding assistants such as Copilot, Cursor, or Claude.
- Ability to evaluate cost, latency, quality, deterministic behavior, and agent-versus-workflow trade-offs.
- Ability to turn ambiguous AI problems into shippable pieces with clear evaluation criteria.
- Clear communication with product teams, stakeholders, and leadership about AI capabilities and limitations.
- Interest in blockchain investigations and financial crime prevention.
Nice-to-Haves
- Retrieval-augmented generation (RAG) and vector databases such as pgvector or Pinecone.
- Multi-agent systems and agent orchestration patterns.
- LLM observability tools such as LangSmith, Langfuse, or Arize.
- Multiple model providers, including Anthropic, OpenAI, and open-weight models, or fine-tuning.
- Terraform, Kubernetes, or infrastructure-as-code tooling.
- Observability platforms such as Datadog.
- Distributed or event-driven architectures using SNS or SQS.
- Cryptocurrency, blockchain, or compliance experience.
Compensation and Benefits
- Hybrid working and the option to work from almost anywhere for up to 90 days per year.
- £500 remote working budget.
- $1,000 learning and development budget.
- 25 days of annual leave plus bank holidays.
- Additional day off for your birthday.
- Enhanced parental leave, including 16 weeks of fully paid leave for eligible employees.
- Private health insurance through Vitality.
- Spill mental health support.
- Life assurance covering four times salary.
- Cycle to Work Scheme.
Skills
TypeScript, Node.js, LangChain, LangGraph, Llm Evaluation, Prompt Engineering, RAG, Vector Databases, AWS, AWS Lambda, ECS, S3, Postgres, Terraform, Kubernetes
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