Job Summary

We are seeking a Senior AI Engineer on 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 up-to-date 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 framework) 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

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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