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AI/RAG Engineer

CoinMarketCap
CompanyCoinMarketCap
CategoryEngineering
LocationUS
RemoteRemote
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted24 Apr 2026
Last verified12 Aug 2026
SourceThe employer's own careers page (company_site)
Applications are handled by the employer, not by us.Apply on the employer's site →
Description
Job Responsibilities • Building AI search agents — including ReAct, planning, and multi-agent architectures via custom implementation or frameworks like 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. • 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 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 in 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 machine learning 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.