Knowledge Engineering Manager

Position Title: Knowledge Engineering Manager Position Type: Regular - Full-Time ​ Requisition ID: 44036 In every role, McCainers are ambitious, curious, and passionate about creating exceptional work experiences - together. With a customer-first mindset, we make doing business with McCain easy. About the role. The Knowledge Engineering Lead is responsible for owning and evolving McCain’s Context Mesh, the proprietary knowledge layer that powers AI use cases across the enterprise. This role ensures that AI solutions are grounded in accurate, trusted, and business-validated knowledge across commercial, manufacturing, agriculture, supply chain, and corporate domains. Reporting to the VP, Artificial Intelligence, the position leads the organization’s knowledge engineering practice, manages domain-specific knowledge teams, and enables the successful integration of knowledge assets across the McCain AI stack, including Azure, Anthropic foundation models, Distyl technologies, Databricks, SAP, and Salesforce. What you’ll be doing. • Own and continuously evolve the McCain Context Mesh as the foundational knowledge layer supporting enterprise AI solutions. • Define ontology architecture, taxonomy frameworks, metadata standards, and governance processes for McCain’s AI ecosystem. • Lead and develop two domain sub-leads responsible for Commercial/Sales and Agriculture/Supply Chain ontologies. • Establish and enforce knowledge engineering standards, methodologies, and quality controls across all domains. • Coordinate cross-domain alignment and resolve ontology, taxonomy, and semantic modeling conflicts. • Deploy and oversee Knowledge Engineers assigned to active AI use-case pods, ensuring consistent standards and practices while supporting project delivery. • Partner with AI Platform & Engineering teams to integrate the Context Mesh into Distyl’s Distillery, Context Mesh, and Refinery capabilities. • Ensure knowledge assets are grounded in Databricks data platforms and remain accessible, scalable, and reusable across AI applications. • Collaborate with business leaders and subject matter experts to validate ontologies, capture emerging knowledge, and embed real-world workflows into AI solutions. • Work closely with Forward Deployment Engineers, Use Case Governance & Operations, and the Architecture Review Board to ensure knowledge quality, source traceability, Responsible AI compliance, and architectural alignment. • Drive the adoption of reusable knowledge patterns and semantic frameworks across the AI organization. • Measure and improve the impact of knowledge engineering on AI solution accuracy, reliability, and business outcomes. What you’ll need to be successful. • Bachelor’s degree in Computer Science, Engineering, Information Science, Linguistics, or a related field; advanced degree preferred. • 18+ years of experience in knowledge engineering, ontology design, taxonomy management, semantic modeling, master data management, or a related discipline. • 5+ years of people leadership experience managing specialized technical teams. • Deep expertise in ontology design and semantic technologies, including OWL, RDF, SKOS, or equivalent modeling frameworks. • Experience building and managing knowledge graphs, semantic layers, and enterprise knowledge architectures. • Strong understanding of vector embeddings, retrieval-augmented generation (RAG), and knowledge-grounding techniques for AI systems. • Experience working with Databricks or comparable lakehouse and data-platform technologies. • Proven ability to bridge complex business domains with AI, machine learning, and data-driven solutions. • Strong stakeholder management, communication, and influencing skills across both technical and business audiences. • Experience partnering with enterprise architecture, governance, and AI platform teams. • Experience within consumer packaged goods (CPG), food service, agriculture, manufacturing, or comparable enterprise environments is an asset. • Demonstrated ability to build scalable knowledge-management practices that improve AI performance, trustworthiness, and adoption. About the team. The Knowledge Engineering Lead leads McCain’s centralized Knowledge Engineering function and reports directly to the VP, Artificial Intelligence. The role oversees two domain-focused sub-leads responsible for Commercial/Sales and Agriculture/Supply Chain knowledge domains and provides functional leadership to Knowledge Engineers deployed into AI use-case pods. Working in close partnership with AI Platform & Engineering, Forward Deployment Engineering, Use Case Governance & Operations, Enterprise Architecture, and business stakeholders, the team ensures that McCain’s AI solutions are powered by trusted, reusable, and business-relevant knowledge assets that create sustainable competitive advantage. About McCain. Click Here to learn more about McCain and how we provide opportunities to make an impact that matters. Leadership principles. At McCain, our leadership principles guide how we engage with customers, collaborate as a team, and achieve success. We focus on understanding customer needs, driving innovation, empowering people, and taking ownership to clear obstacles and deliver results. AI & Digital Capabilities. At McCain, AI and digital capabilities are part of how we work and innovate. We value curiosity toward emerging technologies and the thoughtful, responsible use of AI-enabled tools to improve outcomes as part of our future-ready culture. The McCain experience. We are McCain. This statement is a testament to our collective strength and our individual value. Your contributions play a vital role in our success. Our winning culture is rooted in authenticity and trust, empowering us to bring out the best in one another. Here, you’ll find opportunities to learn, grow, and thrive. Join us and experience why we’re better together. Our purpose is grounded in building meaningful relationships. We’re big believers in the power of working together in person—it helps us stay connected, collaborate more effectively, and grow as a team. At the same time, we recognize the importance of flexibility. Most office-based roles follow a hybrid model, with the option to work remotely two days a week. There may be exceptions depending on the role and location, so we encourage you to speak with your recruiter for more details. McCain Foods is an equal opportunity employer. As a global family-owned company, we strive to be the employer of choice in the diverse communities around the world in which we live and work. We recognize that inclusion drives our creativity, resilience, and success and makes our business stronger. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, age, veteran status, disability, or any other protected characteristic under applicable law. McCain is an accessible employer. If you require an accommodation throughout the recruitment process (including alternate formats of materials or accessible meeting rooms), please let us know   and we will work with you to find appropriate solutions. Your privacy is important to us. By submitting personal data or information to us, you agree this will be handled in accordance with McCain’s Global Privacy Policy  and Global Employee Privacy Policy , as applicable. McCain leverages AI in the hiring process, though all final decisions are made by humans. You can understand our approach to AI and how your personal information is being handled here . Job Family: Information Technology Location(s): IN - India : Haryana : Gurgaon Company: McCain Foods(India) P Ltd