Senior Data and AI Engineer (Insurance Domain)

Senior Data and AI Engineer (Insurance Domain)
Location: Philadelphia PA
Position type: Onsite role (need NJ PA based candidates who can join immediately)
Tax type: W2 contract

Candidate should be available to start by next week.

Job Description:
The role owns the full technical stack from the architecture slide: connectors and ingestion framework OneLake Medallion staging GraphDB triple store Vector Index Agentic RAG orchestrator LLM gateway guardrails and the consumption UI with conversational chat SPARQL trace explainability and graph explorer.

Knowledge Graph & Semantic Technologies (Must-Have)

3 years hands-on experience with graph databases (GraphDB 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 (Prot g 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

Data Engineering & Microsoft Fabric (Good to-Have)

Strong Python engineering skills with experience building data pipelines ETL/ELT processes and metadata ingestion frameworks

Experience with Microsoft Fabric ecosystem: OneLake Lakehouse Notebooks Data Factory / pipelines and Medallion architecture (Bronze/Silver/Gold)

Familiarity with JDBC/ODBC connectors REST API integration and file parsing (Excel CSV JSON) for metadata extraction

Experience with Trino Databricks SQL or equivalent federated query engines