Job Summary
The position focuses on spearheading the strategy, architecture, and execution of an enterprise context layer along with data platforms optimized for AI applications. This includes overseeing the development of semantic models, ontologies, knowledge graphs, and effective metadata capabilities, as well as creating reusable contextual data products. The role involves collaborating with various teams across the organization, ensuring secure, reliable access to information for generative AI and agent-based workflows.
Responsibilities
- Lead the development of enterprise context layers and AI-optimized data platforms.
- Oversee the creation of semantic models, ontologies, and knowledge graphs.
- Manage multidisciplinary engineering teams and collaborate with business and governance leaders.
- Establish and uphold standards for secure information access.
- Enhance metadata capabilities and develop reusable contextual data products.
Qualifications
- Bachelor’s degree in a pertinent field.
- Over 10 years of experience in AI/ML, data management, knowledge engineering, or semantic technologies.
- Demonstrated experience leading technical teams and overseeing large-scale enterprise initiatives.
- Proficient in working with semantic models, knowledge graphs, and integrating structured and unstructured data.
- Familiar with data governance, quality standards, and generative AI technologies, including large language models, retrieval-augmented generation, vector search, and agent-based workflows.
