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Kinaxis

Cloud-based supply chain planning platform

Architect – Ontology & AI Innovation

Data ManagementUpdated on Nov 10
Full-timeNo salary listed

About the Job

Requirements

  • A Master's or PhD in Computer Science, Artificial Intelligence, or a related field, together with relevant experience in enterprise software architecture, applied AI, data modeling, knowledge graph or semantic systems, or supply chain technology.
  • Deep practical understanding of enterprise supply chain systems or adjacent operational systems, including their data, data models, connectivity, and use in solving business problems.
  • Strong hands-on experience designing platform-level software, developer tooling, composable capabilities, workbench-style products, prototypes, proof-of-concepts, or early systems demonstrating structured knowledge and agentic AI.
  • Strong data modeling, semantic modeling, ontology, knowledge graph, or knowledge representation experience, applied pragmatically to supply chain and enterprise platform problems.
  • Experience defining reusable architecture patterns, data model governance, semantic or ontology standards, versioning, lifecycle management, and alignment across enterprise domains.
  • Ability to define long-term evolution strategies for agentic enterprise platforms, balancing delivery speed with durable, scalable, and extensible design.
  • Experience applying emerging techniques in agentic AI, knowledge representation, semantic systems, or enterprise data platforms and translating concepts into practical, product-oriented solutions.
  • Ability to architect large-scale graph, semantic, and data platforms that integrate structured, semi-structured, and unstructured data across planning, warehouse, inventory, and other enterprise systems.
  • Hands-on experience with knowledge graph, data, and integration platforms and pipelines, including design, ingestion, transformation, entity resolution, schema or ontology alignment, validation, update patterns, and performance at scale.
  • Ability to drive technical evaluation of emerging graph, semantic, agentic AI, and enterprise data technologies using clear, defensible trade-off analysis.
  • Required hands-on agentic AI and agentic engineering experience, including building software artifacts, applications, plans, evaluators, or workflows using agentic development approaches and GitHub-native engineering practices.
  • Demonstrated ability to identify, evaluate, and apply emerging research and technologies in agentic AI, knowledge representation, semantic systems, and enterprise platforms, translating them into scalable architecture patterns and reusable, composable, extensible product capabilities.
  • Strong technical judgment and ability to evaluate emerging semantic, graph, agentic AI, enterprise integration, and platform technologies.
  • Demonstrated ability to influence technical direction across product, engineering, platform, and customer-facing domains through expertise, credibility, and collaboration.
  • Ability to communicate complex concepts clearly and align stakeholders across AI, supply chain systems, enterprise data, platform architecture, and product strategy.
  • Ability to distinguish platform architecture from customer-specific implementation and build reusable machinery that downstream teams can configure and extend.
  • Ability to define quality architecture for agentic systems, including evaluators, validation patterns, constraints, guardrails, and approaches for building high-quality software in an agentic technology environment.

Responsibilities

  • Provide hands-on technical leadership in agentic AI, knowledge graph, semantic, and data modeling architecture while designing platform-level tooling connecting Maestro and planning data with broader enterprise systems such as warehouse management, inventory, Salesforce, and partner agentic environments.
  • Design underlying data, graph, and integration architecture, including ingestion pipelines, transformation and mapping, entity resolution, schema alignment, validation, batch and streaming updates, and patterns that allow agents to traverse enterprise data and graph structures.
  • Contribute to key technical decisions across platform architecture, graph architecture, data modeling, AI integration, agentic workflows, quality evaluators, constraint validation, and query-time reasoning at scale.
  • Mentor others and help build a culture of structured thinking, semantic clarity, pragmatic platform architecture, agentic engineering, and product-oriented innovation.

Desired Qualifications

  • Experience with semantic technologies such as RDF, OWL, SHACL, or SPARQL.
  • Background in temporal modeling, digital twins, operational intelligence systems, or enterprise orchestration platforms.
  • Experience contributing to research, standards, open-source projects, or innovation in semantic systems, applied AI, agentic AI, or enterprise data platforms.
  • Experience with enterprise SaaS products and operating AI, graph, data, or agentic platforms at scale.
  • Experience with retrieval-augmented generation (RAG), large language model (LLM) applications, explainable AI, evaluators, or agentic quality frameworks.

About the Company

Kinaxis

Cloud-based supply chain planning platform

Kinaxis provides supply chain management software centered on its RapidResponse platform. The platform offers tools for control towers, operational planning, supply planning, demand planning, and inventory management, all designed to run concurrent planning so organizations can align sales and operations and make fast, data-driven decisions in minutes rather than days. Kinaxis uses a subscription-based model and offers consulting and implementation services, generating revenue from software access and services. The company differentiates itself through concurrent planning that integrates multiple planning domains into a single, agile workflow, enabling quick responses in volatile markets and strong visibility across the supply chain. Kinaxis aims to help businesses plan and respond quickly to market changes, improving agility and decision speed for a wide range of industries.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Ottawa, Canada
Founded
1984

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