Senior Data & AI Engineer, Insurance — Graph & LLM RAG

Accord Technologies Inc

Philadelphia (Philadelphia County)

On-site

USD 120,000 - 150,000

Full time

14 days+
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Job summary

Accord Technologies Inc is seeking a Senior Data and AI Engineer with expertise in the insurance domain. The role involves owning the full technical stack including architecture, connectors, graph databases, and AI integration. Candidates should have substantial experience with graph databases, semantic web standards, and building RAG pipelines.

This onsite position is located in Philadelphia, PA, requiring immediate availability for NJ and PA based candidates. Strong Python skills and familiarity with Microsoft's data ecosystem are preferred.

Qualifications

  • 3+ years of hands-on experience with graph databases in production.
  • Experience with semantic web standards and ontologies.
  • Demonstrated experience building RAG pipelines.
  • Hands-on experience with vector databases like Azure AI Search.
  • Ability to operate under accelerated delivery timelines.

Responsibilities

  • Own the full technical stack from architecture to UI.
  • Collaborate with Data Modeller/Ontologist on implementations.
  • Translate conceptual models into technical solutions.

Skills

Graph databases experience
Semantic web standards proficiency
RAG pipeline experience
Embedding and retrieval with vector databases
LLM API integration

Tools

GraphDB
Neo4j
Azure AI Search
Python
Microsoft Fabric

Job description

Accord Technologies Inc is seeking a Senior Data and AI Engineer with expertise in the insurance domain. The role involves owning the full technical stack including architecture, connectors, graph databases, and AI integration. Candidates should have substantial experience with graph databases, semantic web standards, and building RAG pipelines.

This onsite position is located in Philadelphia, PA, requiring immediate availability for NJ and PA based candidates. Strong Python skills and familiarity with Microsoft's data ecosystem are preferred.

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