Knowledge Engineering Manager

The Knowledge Engineering Manager leads McCain’s knowledge engineering practice and owns the Context Mesh, a knowledge layer used to ground enterprise AI applications in trusted, business-validated information. Based in Gurgaon, Haryana, the role reports to the VP, Artificial Intelligence and supports AI use cases across commercial, manufacturing, agriculture, supply chain and corporate domains.

Responsibilities

• Define and evolve ontology architecture, taxonomies, metadata standards, governance processes and quality controls. Resolve cross-domain semantic conflicts and promote reusable knowledge patterns.
• Manage two domain sub-leads covering Commercial/Sales and Agriculture/Supply Chain, and provide functional leadership to Knowledge Engineers working in AI use-case teams.
• Partner with AI Platform & Engineering to integrate knowledge assets with Distyl’s Distillery, Context Mesh and Refinery capabilities. Ground those assets in Databricks data platforms and make them accessible, scalable and reusable across the AI stack, which includes Azure, Anthropic foundation models, SAP and Salesforce.
• Work with business experts to validate ontologies and represent operational workflows. Coordinate with engineering, governance and architecture teams on knowledge quality, source traceability, Responsible AI compliance and architectural alignment. Measure effects on AI accuracy, reliability and business outcomes.

Required qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Science, Linguistics or a related field; 18+ years in knowledge engineering, ontology design, taxonomy management, semantic modeling, master data management or a related discipline; and 5+ years leading specialized technical teams.
• Expertise in ontology design and semantic technologies such as OWL, RDF or SKOS; experience with knowledge graphs, semantic layers and enterprise knowledge architectures; and understanding of vector embeddings, RAG and AI knowledge-grounding techniques.
• Experience with Databricks or comparable data platforms, cross-functional enterprise teams, stakeholder communication, and scalable knowledge-management practices.

Preferred

An advanced degree and experience in consumer packaged goods, food service, agriculture, manufacturing or comparable enterprise environments are assets. The posting describes a general hybrid approach for most office-based roles, with two remote days weekly, but notes that arrangements may vary by role and location.