Senior AI Engineer

Job Description

• We are seeking a Senior AI Engineer on the Enterprise Intelligence Factory team to play a foundational role in building the enterprise Semantic Ontology & Dimension Factory Platform. This platform enables AI‑ready analytics by combining semantic ontologies, knowledge graphs, agentic AI, and data engineering to automatically generate business‑ready star schemas from heterogeneous enterprise data sources. In this role, you will design and implement agent‑driven pipelines that leverage RDF/OWL ontologies, SPARQL, and Large Language Models (LLMs) to perform semantic alignment, dimension mining, and AI‑assisted data modelling at scale. You will work at the intersection of AI, semantics, and modern data platforms, helping establish engineering patterns and best practices for the team. This is a hands‑on, senior individual-contributor role, ideal for engineers who enjoy building core platform capabilities rather than isolated experiments. Key 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. Required Skills & Qualifications 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.   The hiring manager has flexibility to hire across several levels of seniority. The level will be determined by the selected applicant's skills and competencies. #LI-TE1   Skills Agentic AI, Agentic
• Design, AI Frameworks, Large Language Models (LLMs), LLM Guardrails, LLM Orchestration, Ontology, Python (Programming Language) Compensation Compensation offered for this role is 100,000.00 - 170,500.00 annually and is based on experience and qualifications. The candidate(s) offered this position will be required to submit to a background investigation. Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. One where you can shape the future of protection while supporting causes that mean the most to you. Joining our team means being part of something bigger – a winning team making a meaningful impact. Allstate generally does not sponsor individuals for employment-based visas for this position. Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component. For jobs in San Francisco, please click “ here ” for information regarding the San Francisco Fair Chance Ordinance. For jobs in Los Angeles, please click “ here ” for information regarding the Los Angeles Fair Chance Initiative for Hiring Ordinance. To view the “EEO Know Your Rights” poster click “ here ”. This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs. To view the FMLA poster, click “ here ”. This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint. It is the Company’s policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee’s ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee's terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.