Data Engineer with AI

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