Senior AI Engineer
Core
Design, develop, and support agentic AI pipelines that automate semantic mapping, dimension mining, and ontology-led reasoning to generate AI-ready analytics and business-ready star schemas.
Role type
Senior individual-contributor AI engineer (semantic ontologies & knowledge graphs)
Builds
Enterprise ontologies in RDF/OWL, LLM-powered services for schema comprehension and enrichment, SPARQL querying layers, and Python-based microservices combining semantic reasoning with data engineering.
Domain
Insurance (Allstate) + Semantic Web / Knowledge Graphs / Generative AI
Deliverable
production ML models | product features
Required skills
Python, GenAI/LLM development, RDF/OWL ontologies, SPARQL, knowledge graphs, agentic AI frameworks (Google ADK, LangChain), ETL/ELT, star schemas, metadata-driven pipelines, cloud platforms (Azure/Fabric), analytical problem-solving.
Preferred skills
Enterprise data models (CIM), ontology mapping, data cataloguing, LLMOps, MLOps, model evaluation, AI observability, distributed systems, CI/CD, containerization, AI-assisted analytics.
Technologies
Azure, Fabric, Python, RDF, OWL, SPARQL, SQL, Spark, LangChain, Google ADK, microservices
Responsibilities
Design and evolve enterprise ontologies aligned to CIM; build LLM-powered services for semantic alignment and metadata generation; implement SPARQL reasoning layers; architect Python microservices and batch workflows; build dimension/fact generation pipelines on Microsoft Fabric; define engineering standards and reusable components; partner with data architects and SMEs to validate semantic definitions; conduct code reviews and mentor engineers.
Seniority
Senior, hands-on IC with mentorship responsibilities