Product Manager

Web Checkout and QWare are two software companies in the Volaris Group family, part of Constellation Software. Web Checkout runs equipment checkout, asset lending and resource scheduling for university media centers, libraries, film schools, makerspaces and labs. QWare is a maintenance management system for the people who keep school districts, municipal buildings and other public facilities running: work orders, assets, preventive maintenance, inventory, event scheduling, and a mobile app for the field.

Both are led from Asset Works' product and development organization. We are a buy-and-hold software group, which means we build for the long term and invest in products our customers will still be running a decade from now.

Two products. Two small development teams that have asked for a product manager. No product manager yet. That is the opening.

• Own product direction, discovery, requirements and outcome measurement for Web Checkout and QWare.
• Take over Web Checkout's customer feedback program and make it whole: add the sales and customer success inputs it is missing, and close the loop on what happened after each release.
• Stand up product discovery and feedback intake at QWare where none exists today: find the customers with the richest signal, talk to them, and turn what you hear into a roadmap.
• Make the calls the teams cannot make on their own, with evidence, in writing, framed with your manager in year one. QWare's backlog holds a good example: invest in event and facility-use scheduling, or in building automation integration? Someone has to decide.
• Write PRDs, stories and acceptance criteria that two-person development teams can build from without a second meeting; groom both backlogs; own the trade-offs.
• Measure outcomes. Every major feature gets a named success metric before it is built and a check-in 90 days after it ships. One of your first jobs is to find out what became of a module that shipped a year ago on a customer success recommendation.
• Build the enablement kit for sales, support and implementation at each company, and start a regular win/loss review with the account executives.
• Use AI tooling as a daily part of the work, including owning Web Checkout's AI "product manager" agent profile: what it does well, where a human decision is required, how its output is reviewed.

• Small teams, direct access. You will talk to the developers who build the product and the people who sell and support it, every week, at both companies.
• Two rhythms. Web Checkout ships two named releases a year (June and December) and tracks work in Jira and Confluence. QWare runs two-week sprints in Azure Dev Ops. You will be comfortable in both.
• AI-native by default. Both teams use agentic tooling in development, and you will have enterprise AI tools for discovery synthesis, drafting and analysis. We care how you use them and how you check them.
• Written decisions. A one-page memo that ends a debate is worth more here than a deck.
• Remote, with a manager who frames the hard questions with you in year one and gives you more room as you earn it.

• Product work you have actually done, in one of two shapes. Either 2 or more years as an Associate Product Manager, Product Owner or Product Manager at a B2B software company, owning a backlog and running discovery with a senior PM above you. Or 3 or more years in solutions engineering, implementation, customer success or support leadership at a software company serving schools, universities, facilities teams or public agencies, where you wrote requirements that shipped, ran customer conversations, and made at least one call about what got built next.
• A prioritization decision you made, or helped make, with incomplete evidence: how you gathered what you could, who disagreed, what was decided, and what happened.
• A story about turning a sales or customer success ask into something a developer could build, and what you learned about the difference between the ask and the problem.
• Enough technical depth to hold your own with engineers on APIs, integrations, data models and multi-tenant SaaS; experience inside Jira, Azure Dev Ops or equivalents.
• Evidence that you care what happened after something shipped, including at least one thing that did not land.
• Daily, practical use of AI tools in product work and a grounded view of where they help and where they do not.
• Clear writing. Clear speaking. The ability to present to an executive and to a two-person development…