Data Engineer with AI
- Tanisha Systems Inc.
2 Days Ago
NA
W2
Philadelphia-PA
3-10 Years
Required Skills: Graph DB, Neo4j, Stardog, Azure AI Search, pgvector, Pinecone, Weaviate, Qdrant, OpenAI GPT, Azure OpenAI
Job Description
- 3+ years hands-on experience with graph databases (Graph DB, Neo4j, Stardog)in a production or advanced PoC context
- Working proficiency with semantic web standards
- Experience loading, validating, and querying ontologies in a triple store environment
- Familiarity with ontology authoring tools (Protege, Metaphactory) sufficient to collaborate with the Data Consultant on model iterations
AI / ML Engineering & LLM Integration (Must-Have)
- Demonstrated experience building RAG (Retrieval-Augmented Generation) pipelines, ideally with agentic orchestration patterns
- Hands-on experience with vector databases (Azure AI Search, pgvector, Pinecone, Weaviate, or Qdrant) for embedding and retrieval
- Experience integrating LLM APIs (Anthropic Claude, OpenAI GPT, or Azure OpenAI) with prompt engineering, guardrails, and citation enforcement
- Familiarity with NL-to-SPARQL or NL-to-SQL generation techniques, including few-shot prompting and schema-grounding approaches
- Understanding of AI safety guardrails: prompt injection defense, output sandboxing, and confidence scoring
Delivery & Collaboration (Must-Have)
- Comfortable operating in an accelerated 8-week delivery timeline with weekly milestone gates and hard dependencies
- Ability to work closely with a Data Modeller/Ontologist to translate conceptual models into working technical implementations
- Experience in financial services or insurance data environments is preferred but not required, provided strong technical depth in the above areas
