Senior Product Manager, AI Operations

Role overview

Workflow and AI strategy

• Understand team processes, handoffs, information needs, and bottlenecks; redesign workflows and prioritize by business impact, feasibility, and operating cost.
• Experiment with foundation models, agents, and AI tools; assess quality, reliability, speed, cost, and data requirements in real workflows.
• Own the roadmap for shared AI capabilities and adoption, balancing business value, technical needs, security, and team maturity.
• Make build, buy, reuse, and stop decisions and deliver in short cycles with continuous feedback.

Building and operating solutions

• Build prototypes and pilot workflows with AI tools, models, agents, APIs, and automation; test with employees and improve based on failures.
• Partner with Engineering to bring validated solutions into dependable production use.
• Set evaluation criteria, human review points, failure handling, monitoring, and ownership for each workflow.
• Involve Engineering, Security, and Legal early in decisions about permissions, privacy, integrations, and production readiness.

Shared capabilities and adoption

• Develop reusable capabilities for agent connections to tools and knowledge, context and permissions, output evaluation, and execution monitoring.
• Partner with Data on trustworthy information and access, and turn successful experiments into maintained capabilities.
• Embed workflows into daily operations with clear responsibilities and human review; support champions, training, hackathons, office hours, and rollouts.
• Measure adoption, time saved, cycle time, quality, errors, and operating cost; use evidence to improve, expand, or retire solutions.

Qualifications

• 6+ years of product management experience, ideally with internal products, platforms, or developer and employee tooling.
• Sustained hands-on use of AI and experimentation with foundation models, agents, and development tools.
• Practical experience building and deploying AI workflows that people use, with an ability to explain their operation, evaluation, limitations, and business impact.
• Technical fluency in model selection, retrieval, tool use, agent orchestration, APIs, evaluation, and access controls; able to build and debug prototypes.
• Experience scaling adoption and changing how people work; analytical ability to measure value against a baseline.
• Ability to align functional leaders, collaborate with technical teams, and communicate with colleagues at different levels of AI experience.

Bonus experience

• B2B SaaS operations, CRM or support systems, or internal knowledge tools.
• Building functional champion networks or scaling automations across a company.
• Familiarity with insurance workflows.

Compensation and benefits

• Base pay range is CAD 150,000–CAD 200,000; most hires are around the midpoint, with standout experience potentially placed nearer the top.
• Employee stock options are granted based on experience and are subject to a standard vesting schedule.
• Benefits include health coverage, a CAD 500 lifestyle spending account, four weeks of paid vacation, and parental leave top-ups.
• Employees may work anywhere in the world for up to 60 calendar days per year.

About Quandri