Product AI & Automation Lead

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.
Location  Ottawa and Toronto, Canada - Hybrid
Other Canadian locations - Remote
About

The Role  The Product AI & Automation Lead is responsible for transforming how the Product organization works. This role will identify opportunities to apply AI, automation, and modern tooling across Product workflows and turn them into scalable capabilities that improve speed, quality, decision-making, and organizational effectiveness.
Working within Product Operations & Excellence, you will partner with Product, IT, Security, Data, and R&D teams to redesign how Product work gets done. You will build and scale AI-enabled workflows, agents, automations, integrations, and operating practices that help Product teams spend less time on administrative work and more time creating customer value.
Success will be measured through tangible improvements in Product velocity, capacity, adoption, workflow efficiency, and quality of decision-making.
Vacancy Status:
This is an existing job vacancy
What you will do   Identify and prioritize high-value opportunities across discovery, customer insight, strategy, planning, requirements, execution, launch, reporting, and knowledge management.
Create and deploy workflows, agents, automations, templates, and lightweight internal tools, taking solutions from concept through prototype, adoption, and scaled use.
Connect and simplify the systems where Product work happens, and partner closely with IT / Security to enable the right permissions to get work done in AI tools like Microsoft 365 Copilot, and Claude Code.
Create reusable patterns and trusted shared context so Product work, customer signals, decisions, and learnings are easier to find, update, and reuse by both people and AI systems.
Analyze current ways of working and redesign workflows around AI-first, human-in-the-loop execution, rather than only automating existing steps.
Partner with IT, Security, Legal, Data, and R&D to establish needs for access, data handling, and ensure the right guardrails exist to meet company policy.
Evaluate new capabilities using clear build, buy, partner, security, cost, maintainability, and business-value criteria.
Build practical playbooks, demonstrations, office hours, and communities of practice that move teams from personal AI productivity to shared workflows, agents, and automation.
Define baselines, instrument solutions, and report outcomes such as cycle-time reduction, hours returned to teams, adoption and reuse, output quality, process consistency, and employee experience.
What success looks like   A prioritized Product AI & Automation roadmap is tied to the organization’s highest-value opportunities and biggest sources of friction.
Multiple end-to-end workflows are in regular use and show measurable improvements in speed, capacity, quality, or decision-making.
Product teams have trusted shared context, reusable agents and automations, and clear patterns for safely creating and scaling new solutions.
The Product tooling ecosystem is simpler and better connected, with clear ownership and a repeatable path from experiment to enterprise capability.
AI fluency has increased across Product, and successful practices are embedded into everyday operating rhythms rather than remaining isolated experiments.
What we are looking for   7+ years of experience in Product Operations, Product Management, business systems, digital transformation, or a related discipline within a complex technology organization.
A demonstrated record of turning ambiguous operating problems into shipped tooling, automation, or workflow improvements with measurable results.
Hands-on fluency with generative AI, copilots, agents, workflow automation, APIs and integrations, structured data, and rapid…