Caseware is one of Canada's original Fintech companies, having led the global audit and accounting software industry for over 30 years, with more than 500,000 users across 130 countries and available in 16 different languages. While you might not have heard of us (yet) over 36,000 accounting and audit professionals list Caseware as a skill on their LinkedIn profiles!
We’re looking for a high-agency builder-operator to drive execution across product and cross-functional initiatives. This role is focused on turning defined problems into delivered outcomes fast.You’ll thrive here if you’re a self-learner, highly adaptable, and take extreme ownership, especially in ambiguous, fast-moving environments. Many strong fits for this role come from startup or founder-led teams, where they’ve had to figure things out, wear multiple hats, and drive outcomes with minimal structure.
❗This is a full time position.
❗ This is a New role.
📍 Location:
This is a hybrid role requiring the successful candidate to work 3 days a week in our Toronto office, located at 351 King St E , Toronto, ON.
What you will be doing:
Own end-to-end execution of defined product and business initiatives
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.
Break down ambiguous asks into clear plans, milestones, and deliverables
Drive cross-functional alignment across product, engineering, design, and business teams
Proactively identify and remove blockers to keep work moving
Ensure tight follow-through, nothing falls through the cracks
Track progress and maintain high delivery velocity across multiple workstreams
What you Bring:
3+ years of experience in tech/product roles with strong execution ownership
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.
Strong track record of building and shipping (0→1 projects, internal tools, automations, or similar)
High ownership mindset—you don’t wait for instructions, you figure things out
Proven ability to operate in ambiguous, fast-changing environments
Excellent at structuring chaos into actionable plans
Strong stakeholder management and cross-functional coordination skills
Ability to drive outcomes without direct authority
Experience working closely with founders, senior leadership, or lean teams is a strong signal
Experience in startups or high-growth environments, operating with limited structure and wearing multiple hats is a strong plus
A self-learner who can quickly pick up new domains, tools, and contexts