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AI/RAG engineer

2 hours, 1 minute ago
Anywhere, United Arab Emirates, Singapore, Hong Kong
Full-time
Mid Level
AI (Artificial Intelligence)
Software Development
Machine Learning OpenSearch Python PyTorch React TensorFlow
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CoinMarketCap

CoinMarketCap

CoinMarketCap is the leading source for crypto market data, providing accurate and unbiased information for users to make informed decisions in the cryptocurrency space.

IT Services
11-50
Founded 2013
View All Jobs 17

Description

  • Build AI search agents using ReAct, planning, and multi-agent architectures through custom implementations or frameworks such as LangGraph, Dify, or CrewAI.
  • Build end-to-end RAG pipelines covering ingestion, chunking, embeddings, and hybrid vector search, ideally with OpenSearch.
  • Operate and monitor vector and hybrid indexes in production environments.
  • Implement grounding and citation mechanisms to link generated answers back to their source passages.
  • Automate evaluation using synthetic QA, retrieval-hit-rate tracking, and model-critique loops to measure accuracy and detect drift.
  • Orchestrate external tools and knowledge bases while monitoring latency and cost at production scale.

Requirements

  • 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 of building and optimizing end-to-end RAG pipelines.
  • Experience developing AI search agents with frameworks like ReAct, LangGraph, Dify, or CrewAI.
  • Hands-on experience with OpenSearch or similar vector search technologies.
  • Proficiency in Python and relevant machine learning frameworks such as PyTorch or TensorFlow.
  • Strong understanding of data ingestion, chunking, embeddings, and hybrid vector search techniques.
  • Experience monitoring and managing production environments.
  • Knowledge of grounding and citation techniques in AI-generated content.
  • Familiarity with synthetic QA datasets and evaluation metrics.

Interested in this position?

Apply directly on the company website

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