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

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