AI Innovation Architect – Knowledge Graphs & Ontology

About Kinaxis

Are you looking to join an innovative, market-leading company where you can truly elevate your career? At Kinaxis we are serious about culture, we are serious about technology, we are serious about customers, and we are serious about not taking ourselves too seriously. If you are looking to be part of an incredible growth story, then we might just be the place for you!

In 1984, we started out as a team of three engineers. Today, we have grown to become a global organization with over 2000 employees around the world, 6 global office and a best-in-class HQ in Ottawa, Canada. As winners of several Top Employer awards globally, we are proud to work with our customers and employees towards solving some of the biggest challenges facing supply chains today.

Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains, and supporting the people who manage them. Our powerful, AI infused platform provides full transparency and visibility across end-to-end supply chains, enabling our customers to make faster, better decisions. We are trusted by renowned global brands to provide the agility and predictability needed to navigate today’s volatility and disruption.

With more than 40000 users in over 100 countries, we are expanding our team as we continue to innovate and revolutionize how we support our customers.

Ottawa and Toronto, CA
- Hybrid

Other Canadian locations
- Remote

The AI team is responsible for advancing machine learning solutions in the supply and demand space across industries such as Retail, Consumer Packaged Goods, and Life Sciences. Our work spans forecasting, optimization, replenishment, recommendation, explainability, and emerging AI techniques that help customers solve complex, real-world planning challenges.

What makes this team unique is that we operate at the intersection of applied research, product innovation, and customer impact. We explore new methods, develop novel approaches, and turn them into practical capabilities that can shape the future of the Kinaxis platform. This is a team for people who want to work on meaningful problems, push the boundaries of applied AI in real business settings, and see their ideas influence products used by customers around the world.

This is an existing job vacancy

You bring deep expertise in knowledge representation, semantic systems, and applied AI, and you are energized by translating complex enterprise domains into structured, machine-understandable models. You are comfortable working through ambiguity and building early systems that demonstrate clear value.

You own the enterprise knowledge model including entities, relationships, actions, constraints, and how they evolve over time. You define and govern ontology standards, ensuring clear layering, reuse, and consistency across systems.

You provide technical leadership while remaining hands-on in semantic architecture and knowledge graph development. You design and evolve enterprise knowledge graph platforms that integrate structured, semi-structured, and unstructured data, enabling reasoning, inference, and contextual retrieval.

You design the underlying data and graph architecture, including ingestion pipelines, transformation and mapping, entity resolution, schema alignment, validation, and both batch and streaming updates.

You guide key technical decisions across ontology design, graph architecture, and AI integration, including trade-offs between materialized inference, constraint validation, and query-time reasoning  partner closely with product and engineering to ensure models are practical, scalable, and aligned to real-world use cases.

You will mentor others and help build a culture of structured thinking, semantic clarity and innovation.

• PhD in Computer Science, Artificial Intelligence, Knowledge Representation, or a related field.
• Extensive experience modeling complex domains, with a track record of building enterprise ontologies and knowledge graph systems in production.
• Strong hands-on experience building prototypes, proof-of-concepts, and early semantic systems…