Senior Product Manager, AI Innovations Team, Operations Orchestration

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 Ottawa and Toronto, CA - Hybrid Other Canadian locations - Remote About the role This role owns how Kinaxis prices, packages and sells operations orchestration, and works inside the product closely enough to make those calls from first-hand knowledge of how it is built and what it costs to run. It suits a product manager who has built with large language models themselves and has been accountable for a pricing model or a revenue number. Vacancy Status This is an existing job vacancy What you will do Monetization   Own pricing and packaging for operations orchestration: the unit of value, what is metered, the tiers, per-solution subscriptions, and how third-party model and connector costs are passed through. Build and maintain the unit-economics model from cost-to-serve upward: model tokens and compute per completed agent run, environment sizing, partner pass-through, and forward-deployed engineering effort per phase. Set price floors and margin targets from it working with Kinaxis Finance team. Define the metering and usage attribution the platform must emit (per tenant, per solution, per agent run) and work with engineering to build it. Support Finance, Legal and Sales team structure commercial product terms: conversion terms to production, and partner and reseller terms. Track how changes in model price and capability move cost-to-serve, and adjust pricing, packaging and roadmap accordingly. Go-to-market   Define the product go-to-market motion for operations orchestration Support the creation of the product enablement material that sales, pre-sales and forward-deployed engineers use Represent the product in executive conversations with customers, with system integrators and connectivity partners. Own the commercial metrics: conversion rate, time from dev to production, revenue per customer, and gross margin per solution. Make sure the instrumentation exists to report them. Platform product   Own the requirements for capabilities such as tenancy and environments, entitlements, usage metering, solution packaging, and the governance controls customers buy on. Work inside the build: use the platform, read run traces and evaluation results, join customer co-build sessions with forward-deployed engineers, and turn repeated one-off requests into reusable platform capability. Communicate strategy, roadmap, progress and risks to executive audiences. Assess and mitigate security, privacy and compliance risk with Security and Legal. What we are looking for 7+ years of product management in enterprise SaaS or platform software, including accountability for a product's pricing, packaging or revenue number. You were the person who owned the outcome. Have priced a usage-based or consumption-based product, or a platform sold as capacity plus applications, and built the unit-economics model behind the price. Have built with large language models yourself in the last 12 months: called a model API, built an agent that uses tools, written evaluations, or shipped with an agentic coding tool. You can show what you built. Can explain, without preparation, how an agent decides which tool to call, why evaluations gate a release, what drives token cost and latency, and where retrieval, knowledge graphs and fine-tuning each apply. Technically fluent in enterprise platforms: APIs, authentication and single sign-on, multi-tenancy, event-driven systems and data pipelines. You read an API specification or an architecture document and make calls on it with engineers. Pull your own data with SQL or an equivalent, to define a metric, build a funnel or size a market. Have taken a B2B product to market: launch, sales enablement, and direct work with sales teams on live deals. Bachelor's degree in Computer Science, Engineering, Data Science, Operations or a related field, or equivalent experience. An MBA or advanced degree is an asset. Willing to travel up to 20%. Preferred Qualifications Domain experience in supply chain, manufacturing or operations (planning, S&OP, procurement, logistics), or with ERP, WMS or PLM data models. Experience with enterprise build or data platforms Worked as, or alongside, forward-deployed or solutions engineers on customer builds. Worked on metering, billing, entitlements or cloud marketplace channels. Experience with ontology or semantic modeling, knowledge graphs, or industry reference models such as SCOR. Sold into enterprises where security and compliance (SOC 2, ISO 27001, data residency) are critical Is this role for you You are li