Product Manager, AI Products

What you will be doing:

Drive high-impact AI initiatives within the Caseware platform transformation — shape priorities and sequencing for your workstream, grounded in user research, domain expertise, and a clear view of technical feasibility.

Design and run rigorous eval frameworks: build golden datasets, define task taxonomies, write rubrics that score AI outputs the way a senior practitioner would, and run structured eval cycles before and after every major release.

Work daily with engineering to translate precise problem statements into well-scoped product requirements — including clear acceptance criteria and eval bars before development begins.

Embed with domain experts and partner accounting and audit firms to validate AI outputs against professional standards — not just user preferences, but what a qualified practitioner would actually sign off on.

Drive continuous discovery with practitioners: shadow workflows, test prototypes in context, and turn 'this doesn't feel right' into specific, actionable failure modes.

Stay ahead of the AI landscape — monitor model developments, new architectures, emerging agent patterns, and competitor moves, and bring a clear point of view on what matters for Caseware.

Define and own product health metrics for AI features: task completion, correction rates, override frequency, trust signals, and time-to-completion — and use them to drive product decisions.

Synthesize signals across engineering, partners, domain experts, customer success, and leadership into a coherent product direction — and communicate it with clarity at every level of the organization.

What you will bring:

4+ years of experience in technology-focused product management or product development, including 1–2 years working deeply with AI or machine learning–driven products.

Direct experience building and running eval frameworks for AI products — golden datasets, rubrics, human-in-the-loop validation, and regression tracking across releases.

Technical fluency in LLMs, RAG, prompt engineering, embeddings, and agentic patterns — enough to have substantive conversations with engineers and know when a product problem is a model problem.

High agency: you identify what needs to happen, move without waiting to be told, and take ownership of outcomes rather than just activities.

Genuine curiosity about AI — you follow model releases, read research, understand what frontier labs are shipping, and form your own views on what matters.

Experience working with domain experts or subject matter specialists to define quality bars in high-stakes, regulated, or professional-grade contexts.

Comfortable with ambiguity. Many of the problems this role works on do not have clear playbooks — you are energized by that, not slowed down by it.