AI Innovation Architect – Knowledge Graphs & Ontology
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Key skills for this role
About the Role
Kinaxis is seeking an AI Innovation Architect to own the enterprise knowledge model and lead the design of knowledge graphs and ontologies for supply chain orchestration.
Key Skills for This Role
Responsibilities
- Own the enterprise knowledge model including entities, relationships, actions, constraints, and how they evolve over time
- Define and govern ontology standards, ensuring clear layering, reuse, and consistency across systems
- Provide technical leadership while remaining hands on in semantic architecture and knowledge graph development
- Design and evolve enterprise knowledge graph platforms that integrate structured, semi structured, and unstructured data, enabling reasoning, inference, and contextual retrieval
- Design the underlying data and graph architecture, including ingestion pipelines, transformation and mapping, entity resolution, schema alignment, validation, and both batch and streaming updates
- Guide key technical decisions across ontology design, graph architecture, and AI integration, including trade offs between materialized inference, constraint validation, and query time reasoning at scale
- Partner closely with product and engineering to ensure models are practical, scalable, and aligned to real world use cases
- Mentor others and help build a culture of structured thinking, semantic clarity and innovation
Requirements
- 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
- Deep expertise in ontology design and semantic modeling, including entities, relationships, constraints, and temporal or event based modeling
- Experience defining ontology governance, versioning, and lifecycle management
- Ability to define long term evolution strategies for the enterprise knowledge model and platform
- Experience applying research and emerging techniques in knowledge representation, semantic systems, or AI
- Architect large scale enterprise knowledge graphs that integrate structured, semi structured, and unstructured data
- Hands on experience with knowledge graph platforms and pipelines, including designing, ingestion, transformation, entity resolution, schema/ontology alignment, validation and performance at scale
- Drives the technical evaluation of emerging graph, semantic, and AI technologies with clear, defensible trade off analysis
- Understanding and familiarity of modern AI approaches such as agentic systems, LLMs, RAG, and explainable AI
- Strong programming ability (e.g., Python) and experience with modern data, graph, and cloud platforms
Full Job Posting
About Kinaxis
- Kinaxis is a global leader in modern supply chain orchestration, powering complex global supply chains.
- Our AI infused platform provides full transparency and visibility across end to end supply chains.
- We are trusted by renowned global brands and have over 2000 employees worldwide.
About the Team
- The AI team advances machine learning solutions in 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.
- We operate at the intersection of applied research, product innovation, and customer impact.
What you will do
- 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 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 at scale.
- You 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.
What we are looking for
- 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 that demonstrate the value of structured knowledge.
- Deep expertise in ontology design and semantic modeling, including entities, relationships, constraints, and temporal or event based modeling.
- Experience defining ontology governance, versioning, and lifecycle management, and driving reuse and alignment across domains.
- Ability to define long term evolution strategies for the enterprise knowledge model and platform, balancing delivery with durable design.
- Experience applying research and emerging techniques in knowledge representation, semantic systems, or AI, with a track record of translating new concepts into practical, product oriented solutions.
- Architect large scale enterprise knowledge graphs that integrate structured, semi structured, and unstructured data.
- Hands on experience with knowledge graph platforms and pipelines, including designing, ingestion, transformation, entity resolution, schema/ontology alignment, validation and performance at scale.
- Drives the technical evaluation of emerging graph, semantic, and AI technologies with clear, defensible trade off analysis.
- Understanding and familiarity of modern AI approaches such as agentic systems, LLMs, RAG, and explainable AI, with the ability to integrate structured knowledge effectively.
- Demonstrated ability to identify, evaluate, and apply emerging research and technologies in knowledge representation, semantic systems, and AI, translating them into scalable architecture patterns and product capabilities.
Nice to Have
- Deep experience with semantic technologies (e.g., RDF, OWL, SHACL, SPARQL).
- Experience in supply chain, planning, or other complex operational domains.
- Background in temporal modeling, digital twins, or operational intelligence systems.
- Experience contributing to research, standards, or innovation in semantic systems or applied AI.
- Experience with enterprise SaaS environments and operating semantic/AI platforms at scale.
Work With Impact
- Our platform directly helps companies power the world’s supply chains.
- We work with Fortune 500 brands including Lockheed Martin, Unilever, P&G, ExxonMobil, Cisco and more.
- Social Responsibility: Diversity, Equity, and Inclusion Committee, sustainability net zero operations strategy, community involvement.
- Perks: Flexible vacation and Kinaxis Days, flexible work options, physical and mental well being programs, virtual fitness classes, mentorship programs, training, career development, recognition programs, referral rewards, hackathons.
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