Overview

Join to apply for the AI/RAG engineer role at CoinMarketCap.

Responsibilities

• Building AI search agents, including ReAct, planning, and multi-agent architectures, via custom implementations or frameworks such as LangGraph, Dify, or CrewAI.
• Building end-to-end RAG pipelines from ingestion, chunking, embeddings, and hybrid vector search, ideally using OpenSearch.
• Operating and monitoring vector/hybrid indexes (e.g., OpenSearch) in production environments.
• Implementing grounding and citation to link generated answers back to their exact source passages.
• Automating evaluation using synthetic QA, retrieval-hit-rate tracking, and model-critique loops to continuously measure accuracy and detect drift.
• Orchestrating external tools or knowledge bases and monitoring latency and cost at production scale.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 3+ years of experience developing AI systems, with a focus on retrieval-augmented generation RAG.
• Proven track record in building and optimizing end-to-end RAG pipelines.
• Experience with AI search agent development using frameworks like ReAct, LangGraph, Dify, or CrewAI.
• Hands-on experience with OpenSearch or similar vector search technologies.
• Proficiency in Python and relevant ML frameworks (e.g., PyTorch, TensorFlow).
• Strong understanding of data ingestion, chunking, embeddings, and hybrid vector search techniques.
• Experience with monitoring and managing production environments.
• Knowledge of grounding and citation techniques in AI-generated content.
• Familiarity with synthetic QA datasets and evaluation metrics.

Seniority level

• Not Applicable

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• Information Services

Location: London, United Kingdom