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AI Engineer (Up to 12k)

Summary

Build and improve AI-powered intent tools using LLM frameworks, vector databases, and microservices to automate knowledge base creation and quality control for chatbots.

Tasks



  • Build an AI-powered intent generation tool that extracts intents and answers from PRDs, and generates sample user queries to help the CS team build RAG knowledge bases more efficiently.

  • Develop an intent similarity detection pipeline using semantic search to identify duplicate or highly similar intents, and integrated it into the intent generation workflow for knowledge base quality control.

  • Enhance the intent management platform by implementing review and approval workflows, production gating, distributed task persistence, and multi-worker task recovery.

  • Researche Voice AI for potential integration into the existing chatbot, evaluating speech recognition, text-to-speech, and system architecture.


Key Skills Required



  • Agentic Frameworks: Hands-on experience with frameworks like LangChain, LangGraph, or, CrewAI

  • LLM Architectures & Tool Use: Expertise in prompt engineering, fine-tuning, function calling/API integration, and evaluation frameworks for LLM-driven agents.

  • Programming & Systems: Advanced Python skills; familiarity with microservices, Docker, REST APIs, and event-driven architectures.

  • Vector Databases & Storage: Proficiency with vector stores (e.g., Pinecone, Qdrant, Chroma, Milvus) for memory persistence and context retrieval.


experience


4 years


skills


Python, SQL, Langchain, LangGraph


qualifications


Bachelors in Computer Science, Data Science, Artificial Intelligence, or Information Technology


education


Bachelor Degree

See also

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