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| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
Coin Market Cap Ltd | Hong Kong, Hong Kong | $92k - $117k | |||
Crypto.com | Hong Kong, Hong Kong | $105k - $120k | |||
Blockchain 121 | New York, NY, United States | $200k - $400k | |||
Base | Remote | $218k - $256k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Caiz | Remote | $80k - $150k | |||
Sentient | India | $104k - $110k | |||
Binance | Asia |
| |||
Chaoslabs | Remote | $144k - $164k | |||
Base | Remote | $218k - $256k | |||
CoinGecko | Singapore, Singapore | $45k - $90k | |||
SwissBorg | Barcelona, Spain | $103k - $112k | |||
Binance | Taipei, Taiwan |
| |||
Binance | Taipei, Taiwan |
| |||
Nearfoundation | Remote | $87k - $112k | |||
Argus Labs | San Francisco, CA, United States | $90k - $145k |
Coin Market Cap Ltd
$92k - $117k estimated
AI/RAG engineer
Global / Hong Kong / Kuala Lumpur / London / Penang / Singapore / Taipei
CMC /
Full-time /
Remote
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Job Responsibilities
1. Building AI search agents- including ReAct, planning, and multi-agent architectures via custom implementation or frameworks like LangGraph, Dify, or CrewAI.
2. Building end-to-end RAG pipelines from ingestion, chunking, embeddings, and hybrid vector search, ideally using Opensearch.
3. Operating and monitoring vector/hybrid indexes (e.g. OpenSearch) in production environments.
4. Implement grounding and citation to link generated answers back to their exact source passages.
5. Automate evaluation using synthetic QA, retrieval-hit-rate tracking, and model-critique loops to continuously measure accuracy and detect drift.
6. Orchestrating external tools or knowledge bases and monitoring latency and cost at production scale.
Qualifications
1. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
2. 3+ years of experience in developing AI systems, with a focus on retrieval-augmented generation (RAG).
3. Proven track record in building and optimizing end-to-end RAG pipelines.
4. Experience with AI search agent development using frameworks like ReAct, LangGraph, Dify, or CrewAI.
5. Hands-on experience with OpenSearch or similar vector search technologies.
6. Proficiency in Python and relevant machine learning frameworks (e.g., PyTorch, TensorFlow).
7. Strong understanding of data ingestion, chunking, embeddings, and hybrid vector search techniques.
8. Experience with monitoring and managing production environments.
9. Knowledge of grounding and citation techniques in AI-generated content.
10. Familiarity with synthetic QA datasets and evaluation metrics.
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What an AI Developer does?
An AI developer is someone who creates and builds artificial intelligence systems
Their responsibilities may include designing and implementing algorithms, creating and training machine learning models, and deploying AI systems to solve practical problems
Additionally, they may be responsible for maintaining and improving existing AI systems, as well as collaborating with other teams or individuals to integrate AI technology into larger systems.