Senior AI Engineer remote type Fully Remote locations USA - IL (Remote) time type Full time job requisition id R29808 At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years, our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection. 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. Preferred Skills: - 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.

• Build and maintain scalable data pipelines using Databricks and Azure Data Lake Storage Gen2 (ADLS Gen2), ensuring reliability and performance across all pipeline stages. • Implement the Medallion Architecture (Raw → Silver → Gold layers) to clean, normalise, and structure technical documentation for downstream AI consumption. • Design and develop the Reasoning Layer using frameworks such as LangChain or LlamaIndex to manage LLM logic, prompt routing, and tool orchestration. • Manage and tune Vector Databases (e.g. Pinecone, Weaviate, or Azure AI Search) to enable fast and accurate semantic retrieval across the corporate knowledge base. • Develop Azure Apps and Azure Functions to connect the AI system to external enterprise platforms such as Salesforce and SharePoint, enabling end-to-end automation.

Role Description Are you passionate about data engineering and ready to revolutionize how data is managed and utilized within an organization? We are looking for a skilled and innovative Analytics Engineer to join our dynamic team and help us implement a cutting-edge Data Mesh architecture. Your daily adventures will include: - Collaborate with cross-functional teams including data analysts, data scientists, and software engineers to understand data requirements and design optimal data solutions in the Data Mesh environment. - Develop, implement, and maintain scalable data products that enable the seamless flow of data from various sources to the Data Mesh architecture. - Create and manage data models that cater to the specific needs of data consumers while adhering to data governance and security standards. - Design and build data quality monitoring frameworks to ensure data accuracy, consistency, and reliability. - Stay updated with the latest industry trends and best practices in Data Engineering and Data Mesh to continuously improve data pipelines and processes. - Build high-performance APIs to access and query data from the data warehouse. - Perform data analysis required to troubleshoot data-related issues and assist in the resolution of data issues. - Coordinate and oversee the successful delivery of complex data engineering projects, ensuring alignment with timelines, objectives, and stakeholders. Qualifications - You have advanced knowledge of at least one programming language and are happy to learn more. Our core languages are Scala and Python. - Expert level of SQL (especially SparkSQL) and Data Warehouse concepts, Database. Experience in building data pipelines is a core requirement. - Love getting your hands dirty with the data implementing custom ETLs to craft it into information. - You have knowledge of distributed systems, Lambda, AWS S3, AWS CloudWatch. - Experience with AWS, Hive, Spark, Trino, Databricks is helpful. - Enjoy working with stream processing frameworks like Spark structured streaming, Kafka streams. - You understand requirements beyond the written word. Your attention to detail leads to a delightful user experience. - Fluent proficiency in Business English. - Exceptional analytical skills, lateral thinking, and experience in solving challenging problems. - Experience working with Data Visualization tools (e.g., Tableau, Metabase) is a plus. Requirements - Advanced knowledge of programming languages (Scala, Python). - Expert level SQL skills (especially SparkSQL). - Experience in building data pipelines. - Knowledge of distributed systems and AWS services. - Experience with stream processing frameworks. - Fluent in Business English. - Exceptional analytical and problem-solving skills. Benefits - Flexible location: Hamburg, Berlin, Barcelona, or Athens. - Work in a multinational, diverse, highly motivated, and collaborative team. - Opportunity to work with cutting-edge technology. - Focus on data-driven decisions that drive business forward.

• AI Feature Development: Design, build, and deploy production-grade AI capabilities into our SaaS product, utilizing RAG pipelines, autonomous agentic tools, and Model Context Protocol (MCP). • Architectural Engineering: Architect and maintain highly scalable, reliable backend solutions using ASP.NET Core and F#, strictly adhering to functional programming principles and event-driven architectures. • Vector & Data Management: Implement and optimize vector databases to ensure ultra-low latency, highly accurate semantic search and contextual data retrieval. • Model Selection & Evaluation: Evaluate, benchmark, and integrate diverse LLMs and foundation models, matching their unique capabilities to specific product requirements for optimal cost, speed, and accuracy. • Cloud & AI Infrastructure: Orchestrate and manage secure, scalable workloads within the Azure ecosystem, specifically leveraging Azure AI deployments.