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AI Conversational Knowledge Retrieval Developer

Evelyn Vestergaard

Full-time · Job · Chicago

About the role

Support teams spend 45 minutes per ticket searching through documentation that should take 90 seconds to find. We've built a conversational knowledge retrieval layer on top of enterprise knowledge bases that answers support questions in plain language, cites the exact source, and escalates when it doesn't know. It reduces tier-1 ticket volume by 38% for our 220 SaaS clients. The system works for common questions. The remaining 62% of tickets — the complex ones — are where we're investing now. These involve multi-hop reasoning across several knowledge base articles, contradictory information in different docs, and questions that require understanding customer account state alongside product documentation. You'll build the retrieval and reasoning improvements that push coverage from 38% to 60%. The team is four engineers and a product manager. You'll own the retrieval quality layer — retrieval strategy, re-ranking, answer grounding, and the confidence signals that decide when to escalate versus answer.

Responsibilities

  • Improve multi-hop retrieval for questions requiring synthesis across multiple documents
  • Build contradiction detection for conflicting information in knowledge base sources
  • Design confidence scoring to determine when to answer versus escalate
  • Implement answer grounding to ensure every response cites its source accurately
  • Create evaluation benchmarks from real support ticket history
  • Monitor retrieval quality across client knowledge bases as they update

Requirements

  • 3+ years building RAG or information retrieval systems
  • Experience with LangChain, LlamaIndex, or similar orchestration frameworks
  • Strong Python and API development skills
  • Understanding of retrieval evaluation metrics: MRR, NDCG, answer accuracy
  • Ability to iterate quickly based on real-world failure analysis

Benefits

  • Fully remote
  • Health and dental
  • 401(k) with match
  • $3,000 professional development budget
  • Flexible working hours

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Categories

NLP & Prompt Engineering Automation & AI Workflows

Skills

python rag langchain openai api fastapi

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

NLP & Prompt Engineering Automation & AI Workflows

Skills

python rag langchain openai api fastapi sql

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