Senior AI Engineer

Allstate Insurance Co. is seeking a Senior AI Engineer to join their Enterprise Intelligence Factory team. The role involves building the enterprise Semantic Ontology & Dimension Factory Platform, enabling AI-ready analytics through the design and implementation of agent-driven pipelines and modern data platforms.

Responsibilities:

• Design, build, and maintain agentic AI pipelines (using Google ADK or similar frameworks) to automate semantic mapping, dimension mining, and ontology-driven reasoning
• Create and evolve enterprise ontologies in RDF/OWL, including upper ontologies and domain extensions aligned to CIM (where applicable), to enable reusable enterprise semantics
• Engineer LLM-powered services for schema understanding, semantic alignment, ontology enrichment, and AI-assisted metadata generation, with a focus on accuracy, traceability, and scale
• Implement SPARQL querying and reasoning layers over knowledge graphs to drive downstream transformations and ensure consistent interpretation of business concepts
• Architect and deliver Python-based microservices and batch pipelines that integrate semantic reasoning with modern data-engineering workflows
• Build and optimize dimension and fact generation pipelines on Microsoft Fabric (Lakehouse, Spark, SQL, orchestration) to produce business-ready star schemas from heterogeneous sources
• Define and enforce engineering standards, design patterns, and reusable components for semantic and AI-driven data platforms (quality, observability, security, and performance)
• Partner with data architects, domain SMEs, and governance teams to validate semantic definitions, manage change, and ensure platform scalability and adoption
• Conduct code reviews, mentor engineers, and influence technical decisions across the platform to raise engineering quality and delivery velocity

Requirements:

• 6+ years of professional software engineering experience, with strong proficiency in Python and GenAI
• Hands-on experience building LLM-based systems using commercial or open-source models
• Solid understanding of semantic technologies: RDF, OWL, ontologies, knowledge graphs, and SPARQL
• Experience designing or working with agentic AI frameworks (e.g., Google ADK, LangChain agents, or similar)
• Strong background in data engineering concepts (ETL/ELT, star schemas, metadata-driven pipelines)
• Experience building and operating systems on cloud platforms, preferably Microsoft Azure / Microsoft Fabric
• Strong problem-solving skills and ability to work in ambiguous, greenfield platform initiatives
• Experience with enterprise data models (e.g., CIM or canonical models)
• Familiarity with semantic alignment, ontology mapping, or data cataloguing tools
• Exposure to MLOps / LLMOps, model evaluation, and AI observability
• Knowledge of distributed systems, CI/CD pipelines, and containerisation
• Experience building AI-assisted analytics or semantic layers for BI or NLQ use cases