Senior AI Product Engineer
HybridLondon, England, United Kingdom
Job Summary
Senior AI Product Engineer responsible for designing and building agentic AI workflows and backend services powering Elliptic's copilot for blockchain investigations. Lead design of agents, tool integrations, and retrieval pipelines; own evaluation frameworks for AI outputs; develop backend services with TypeScript/Node.js; drive architectural decisions; mentor junior engineers; promote testing, observability, and reliability; influence cross-team AI capabilities integration. Requires production experience with LLM-powered features, strong backend skills, and experience with LangChain/LangGraph, cloud (AWS), and observability tooling. Expected impact includes delivering end-to-end significant AI capabilities, setting technical direction for AI workstreams, and growing team practices.
Required Qualifications
- 5-8+ years of software engineering experience
- 1-2 years of 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
- 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.) effectively
- 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 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
Desired Qualifications
- 5-8+ years of software engineering experience
- 1-2 years of 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
- 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.) effectively
- 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 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
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