Group Product Manager, AI Platform

As Group Product Manager for the AI Platform, you sit at the center of the team building Caseware's core AI surfaces — the agents and agent builder practitioners use to do real work, the eval builder and eval roadmap that let us measure quality, and the pods bringing each of these to life. You don't own the AI platform vision alone — that sits with platform leadership — but you make it real: you lead the team of product managers who each own a piece of it, sequence their overlapping roadmaps into one coherent delivery plan, and make sure the whole is moving faster and more coherently than the sum of its parts. 

What makes this role unique is the balance it demands: enough product depth to genuinely partner with each PM on their space, and enough leadership craft to manage, coordinate, and unblock a team of product owners rather than owning a single roadmap yourself. You are the person who turns four parallel workstreams into one delivery story. 

1. Roadmap Delivery & Team Development: Partner with the Principal Product Manager who owns the AI Platform roadmap to keep the roadmap aligned with organizational goals, and drive it to execution. Maintain deep knowledge of AI capabilities, agent patterns, and model limitations relevant to audit work, including how they compare to emerging market solutions. Continually assess and refine the AI product suite, identifying new opportunities for automation within audit workflows and the right resourcing to pursue them. Cultivate deep expertise in AI to grasp the full scope of what's technically feasible, and use that expertise to coach the Principal Product Manager toward greater ownership of roadmap strategy over time. 

1. Influence and Leadership: Foster a culture of process improvement and employee engagement within and across the AI product, engineering, and applied science teams. Mentor team members and other employees, ensuring the inclusion of relevant stakeholders — including audit practitioners — in decision-making processes. Build a supportive culture that empowers teams to take on more responsibility as AI capabilities mature — including actively developing the Principal Product Manager's ability to own strategy and roadmap definition. 

1. Execution and Collaboration: Partner closely with engineering and applied science teams to translate audit pain points into scoped AI features, requirements, and acceptance criteria. Articulate the concept of incremental value delivery to a wide range of stakeholders, including customers, partners, and internal teams. Engage with strategic key accounts and partner firms to understand how AI capabilities are used in practice and what's driving or limiting adoption. Diligently track and proactively manage KPIs and product metrics — including AI accuracy, adoption, and trust — to optimize performance and drive strategic decision-making. 

1. Practitioner Insight and Trust: Champion a culture of data-driven decision-making grounded in real audit practice. Serve as an authority on how practitioners will actually use and judge AI outputs, leveraging that insight for product enhancements. Partner with the Principal Product Manager to define the practitioner-credibility standard for AI outputs — not just whether an output is technically accurate, but whether it meets the bar a qualified auditor would need before relying on it. Ensure consistent integration of practitioner and user research into decision-making, shaping product requirements, design, and development accordingly. 

• 5+ years of product management experience, including experience leading, mentoring, or managing other product managers. 

• Proven ability to coordinate multiple concurrent workstreams with overlapping dependencies, and to resolve conflicts between them without needing to personally own each one. 

• Comfortable operating as an orchestrator and multiplier rather than a sole roadmap owner — your success is measured by the team's throughput and coherence, not just your own output. 

• Experience with AI or ML-driven products strongly preferred; enough technical fluency to have substantive conversations with engineering and applied science. 

• Excellent written and verbal communication — able to turn several parallel workstreams into one clear story for leadership. 

• Confidence making sequencing and prioritization calls under ambiguity, and comfortable being the one who says “no, not yet” to a pod on behalf of the group's overall plan.