AI/RAG engineer
Description For AI/RAG engineer
CoinMarketCap, a leading cryptocurrency data platform, is seeking an AI/RAG Engineer to join their team in a remote capacity. This role sits at the intersection of artificial intelligence and information retrieval, focusing on building sophisticated AI search agents and RAG (Retrieval-Augmented Generation) systems.
The position offers an exciting opportunity to work with cutting-edge AI technologies, including ReAct, LangGraph, and CrewAI frameworks. You'll be responsible for developing end-to-end RAG pipelines, implementing vector search solutions using OpenSearch, and ensuring the accuracy and reliability of AI-generated content through robust evaluation systems.
The ideal candidate brings 3+ years of experience in AI system development, with specific expertise in RAG technologies. Your strong foundation in computer science or AI, combined with hands-on experience in Python and machine learning frameworks, will be essential for success in this role.
Working at CoinMarketCap means being at the forefront of combining AI technology with cryptocurrency data analytics. You'll have the opportunity to shape how millions of users interact with cryptocurrency information through AI-powered solutions. The remote work environment offers flexibility while collaborating with a global team across multiple locations including Hong Kong, Singapore, London, and other major tech hubs.
This role is perfect for someone passionate about AI technology who wants to make a significant impact in the cryptocurrency space. You'll be working on challenging problems involving large-scale data processing, AI model optimization, and production-level system maintenance, all while helping to revolutionize how people access and understand cryptocurrency data.
Responsibilities For AI/RAG engineer
- Building AI search agents including ReAct, planning, and multi-agent architectures
- Building end-to-end RAG pipelines from ingestion, chunking, embeddings, and hybrid vector search
- Operating and monitoring vector/hybrid indexes in production environments
- Implement grounding and citation to link generated answers back to their exact source passages
- Automate evaluation using synthetic QA, retrieval-hit-rate tracking, and model-critique loops
- Orchestrating external tools or knowledge bases and monitoring latency and cost at production scale
Requirements For AI/RAG engineer
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field
- 3+ years of experience in developing AI systems, with 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 machine learning frameworks
- 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
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