Technical Product Manager

What You'll Be Doing • Own the roadmap for one or more data and AI product lines — you set priorities, you defend the trade-offs, and you're accountable for the results.

• Run discovery directly with enterprise clients and internal stakeholders to identify high-value problems worth solving, and separate them from the noise.

• Write clear, decision-ready product requirements: user stories, acceptance criteria, data contracts, edge cases, and what “done” actually means.

• Partner day-to-day with engineering, data engineering, and design to sequence delivery, unblock decisions quickly, and keep scope honest.

• Define success metrics up front, adoption, data quality, time-to-insight, model reliability, cost per outcome, and instrument products so those metrics are observable after launch.

• Lead sprint ceremonies alongside engineering leads and keep delivery predictable without turning the team into a ticket factory.

• Turn client feedback, usage data, and support signals into a prioritized backlog of improvements rather than a list of one-off requests.

• Manage launches end to end: rollout plans, enablement material, internal training, and post-launch review.

• Communicate roadmap status, risks, and trade-offs clearly to senior stakeholders on both the client and ShyftLabs sides.

• Contribute to how we do product here, our discovery practices, prioritization frameworks, and delivery rituals are still being shaped, and we want your input on them.

What You'll Bring • 3–6 years of product management experience, including at least 2 years shipping data, analytics, platform, or AI-powered products.

• A track record of taking products from problem statement to production, not just maintaining an existing backlog.

• Strong technical fluency: you can hold your own in an architecture discussion, read a data model, reason about APIs and integrations, and understand why a pipeline decision has downstream consequences.

• Comfort working with enterprise stakeholders, including the ability to push back constructively on a request that isn't the right thing to build.

• Analytical rigour, you use data to frame decisions and you're honest about what the data doesn't tell you.

• Experience with Agile delivery and modern product tooling (Jira, Confluence, Figma, or equivalents).

• Excellent written communication. Much of the job is writing things down clearly enough that people can act on them.

• Bachelor's degree in Computer Science, Engineering, Business, or a related field, or equivalent practical experience

Nice to Have • Background in retail, commerce media, or retail media networks.

• Familiarity with LLM-based products: RAG, prompt orchestration, tool calling, evaluation frameworks, and guardrails.

• Working knowledge of cloud data platforms such as Databricks, Snowflake, or BigQuery, and how they shape product constraints.

• SQL skills sufficient to answer your own questions without waiting on someone else.

• Prior experience in a startup or client-facing product environment.

Salary Range • $130,000 - $160,000 (CAD)