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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 40,000 users in over 100 countries, we are expanding our team as we continue to innovate and revolutionize how we support our customers.
Location This is a remote position. You can work from home and be located anywhere in UK & Europe region.
About the team
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.
Vacancy Status
This is an existing job vacancy
What you will do
You bring deep expertise in agentic AI, enterprise platform architecture, supply chain systems, data modeling, and knowledge graph or semantic technologies, and you are energized by translating complex enterprise domains into reusable, machine-understandable platform capabilities.
You thrive in a fast-moving, ambiguous, startup-like product environment where agentic engineering dramatically compresses delivery cycles and requires strong judgment, speed, and adaptability.
You provide hands-on technical leadership in agentic AI, knowledge graph, semantic, and data modeling architecture while designing platform-level tooling that can connect Maestro and planning data with broader enterprise systems such as warehouse management, inventory, Salesforce, and partner agentic environments or similar ecosystems.
You design the 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.
You 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.
You will mentor others and help build a culture of structured thinking, semantic clarity, pragmatic platform architecture, agentic engineering, and product-oriented innovation.
What we are looking for
Masters or PhD in Computer Science, Artificial Intelligence or a related field. 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 what data exists in those systems, how it is modeled, how to connect to it, and how it can be used to solve real business problems.
Strong hands-on experience designing platform-level software, developer tooling, composable capabilities, workbench-style products, prototypes, proof-of-concepts, or early systems that demonstrate the value of structured knowledge and agentic AI.
Strong data modeling, semantic modeling, ontology, knowledge graph, or knowledge representation experience, with the ability to apply these skills 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 speed of delivery with durable, scalable, and extensible design.
Experience applying emerging techniques in agentic AI, knowledge representation, semantic systems, or enterprise data platforms, with a track record of translating new concepts into practical, product-oriented solutions.
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.
Drives the technical evaluation of emerging graph, semantic, agentic AI, and enterprise data technologies with clear, defensible trade-off analysis.
Hands-on agentic AI and agentic engineering experience is required, 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 product capabilities that enable reuse, composability, and extensibility across products.
Strong technical judgment and the 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.
Excellent communication skills, with the ability to bring clarity and alignment to complex concepts across AI, supply chain systems, enterprise data, platform architecture, and product strategy.
Ability to distinguish platform architecture from customer-specific implementation, building 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.
Nice to Have
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 RAG, LLM applications, explainable AI, evaluators, or agentic quality frameworks.
#Senior
Work With Impact: Our platform directly helps companies power the world’s supply chains. We see the results of what we do out in the world every day, when we see store shelves stocked, when medications are available for our loved ones, and so much more.
Work with Fortune 500 Brands: Companies across industries trust us to help them take control of their integrated business planning and digital supply chain. Some of our customers include Lockheed Martin, Unilever, P&G, ExxonMobil, Cisco and more.
Social Responsibility at Kinaxis : Our Diversity, Equity, and Inclusion Committee weighs in on hiring practices, talent assessment training materials, and mandatory training on unconscious bias and inclusion fundamentals. Sustainability is key to what we do and we’re committed to a long-term net-zero operations strategy. We are involved in our communities and support causes where we can make the most impact.
People matter at Kinaxis and here are some of the perks and benefits we offer, which may vary by location and employee:
Flexible vacation and Kinaxis Days (company-wide days off)
Flexible work options
Physical and mental well-being programs
Regularly scheduled virtual fitness classes
Mentorship programs, training, and career development
Recognition programs and referral rewards
Hackathons
For more information, visit the Kinaxis website at www.kinaxis.com or the company’s blog at
Kinaxis welcomes candidates to apply to our inclusive community. We provide accommodations upon request to ensure fairness and accessibility throughout our recruitment process for all candidates, including those with specific needs or disabilities. If you require an accommodation, please reach out to us at . This contact information is for accessibility requests only and cannot be used to inquire about the status of applications.
Kinaxis is committed to ensuring a fair and transparent recruitment process. We use artificial intelligence (AI) tools in the initial step of the recruitment process to compare submitted resumes against the job description to identify candidates whose education, experience, and skills most closely match the requirements of the role. After the initial screening, all subsequent decisions regarding your application, including final selection, are made by our human recruitment team. AI does not make any final hiring decisions.