[Hiring] Senior Product Manager, AI Operations @Quandri

Role Description

You will help reinvent how Quandri's teams operate by combining a deep understanding of their work with practical knowledge of what AI can do. We are looking for a systems thinker and hands-on builder who actively experiments with foundation models, agents, and emerging tools, recognizes when new capabilities make a different approach possible, and turns that insight into solutions people will use.

You will own two connected responsibilities: Quandri's internal AI platform and company-wide adoption. The platform will include shared tools, agent infrastructure, evaluation, and guardrails. Adoption means working with functional leaders to redesign workflows, build team capabilities, and make new ways of working effective and sustainable.

Your customers are our teams across Sales, Marketing, Customer Experience, Implementation, Finance, Operations, Product and Engineering. You will discover where work gets stuck, decide which problems are worth solving, and take solutions from prototype to sustained use. You will report to the VP of Product and partner closely with Engineering, the VP of Finance and Operations, Security, and functional leaders.

You should already use AI extensively in your own work and have a clear point of view, grounded in experimentation, on where it is useful and where it falls short. Your success here will show up in sustained, high-quality adoption, faster work, better decisions, and capacity returned to teams. You will also help colleagues become better builders through shared tools, practices, and support.

What You'll Do:

• Rethink how teams work.
• Work directly with teams to understand their goals, processes, handoffs, information needs, and recurring bottlenecks.
• Challenge assumptions about which steps are necessary, where human judgment adds value, and how responsibilities could change.
• Design better workflows with functional leaders, establish a baseline, and prioritize by business impact, feasibility, and ongoing operating cost.
• Translate AI advances into practical opportunities.
• Stay current with foundation models, agent infrastructure, and AI development tools through regular hands-on experimentation.
• Evaluate new capabilities against real Quandri workflows, including their quality, reliability, speed, cost, and data requirements.
• Identify when an advance warrants a new approach and when an existing solution remains the better choice.
• Own the platform and enablement roadmap.
• Translate company priorities and employee research into a focused roadmap for shared AI capabilities and adoption.
• Balance business value, technical and security requirements, and different levels of AI maturity across teams.
• Make clear build, buy, reuse, and stop decisions, and deliver in short cycles with continuous feedback.
• Build and validate.
• Personally build working prototypes and pilot workflows using AI development tools, models, agents, APIs, and automation.
• Connect the information and tools needed to complete useful work, test with employees, and iterate on observed failures.
• Partner with Engineering to take validated solutions into dependable production use.
• Make solutions dependable.
• Define evaluation criteria, human review points, failure handling, monitoring, and ownership for each workflow.
• Involve Engineering, Security, and Legal early in decisions about permissions, data privacy, integration quality, and production readiness.
• Ensure people can understand what an automation did and recover when it fails.
• Create reusable capabilities.
• Shape shared capabilities for connecting agents to tools and knowledge, managing context and permissions, evaluating outputs, and monitoring execution.
• Partner with Data, which owns shared analytics and the integrations roadmap, on trustworthy information and access.
• Turn successful team experiments into maintained capabilities that others can adopt without starting over.
• Lead adoption and change management.
• Work with functional leaders to embed new workflows into daily operations, with clear responsibilities and human review points.
• Build a network of functional champions and use practical training, hackathons, office hours, and rollout support to help teams develop their own capabilities.
• When adoption stalls, diagnose whether the barrier is usefulness, trust, skills, or workflow fit, then adjust.
• Measure business value.
• Track adoption alongside time saved, cycle time, output quality, errors, and total operating cost.
• Validate productivity gains with users and workflow evidence.
• Use those findings to improve, expand, or retire solutions and keep leadership informed about what is working.

Qualifications

• 6+ years of product management experience, ideally including internal products, platforms, or developer and employee tooling, with ownership from discovery through sustained use.
• Systems thinking: you can connect processes, information flows, tools, incentives, and human decisions, and recognize when improving one task simply moves the bottleneck elsewhere.
• A sustained practice of using AI in your own work and testing new foundation models, agent frameworks, and development tools.
• Practical experience building and deploying AI workflows.
• Technical fluency with model selection, context and retrieval, tool use, agent orchestration, APIs, evaluation, and access controls.
• Strong product judgment: you can distinguish an interesting demonstration from a recurring problem worth solving.
• A track record of scaling adoption and changing how people work, including helping teams build skills and take ownership of new workflows.
• Analytical discipline and comfort measuring value against a baseline, including the human effort required to review and correct outputs.
• The ability to align functional leaders, collaborate with technical teams, and explain new ways of working clearly to colleagues with different levels of AI experience.

Bonus Points if You Have:

• Experience with B2B SaaS operations, CRM and support systems, or internal knowledge tools.
• Experience building a network of functional champions.
• Experience taking an automation from one team's experiment to a capability used across a company.
• Familiarity with insurance workflows.

Benefits

• The range for base pay is $150k - $200k CAD, most hires land around the midpoint of the range, while candidates with standout experience may land closer to the top.
• Employee stock options, granted based off experience level upon hire and subject to a standard vesting schedule.
• Comprehensive health benefits, including $500 Lifestyle Spending Account.
• Four weeks of paid vacation per year.
• Work anywhere in the world for 60 calendar days of the year.
• Parental leave top-ups: 6 months for birthing parents, 8 weeks for non-birthing parents (up to $100,000 annual salary).

Our Guiding Principles:

• Customers at the core.
• Move with urgency.
• Be curious.
• Excellence in execution.
• Act like an owner.
• Fight for simplicity.
• AI-first.