Product Manager - AI

Product Manager - AI

**Application Deadline: **31 December 2026

**Reporting To: **VP of Product

Description

You will own the AI side of the PrismCX roadmap. You will turn customer problems and AI opportunities into validated, shippable features, and you will prove value before we commit to building at scale. You think in prototypes, not spec documents: you can take an idea to a working prototype in hours or days, test it with customers, and make a clear call on what to build next.

Key Responsibilities

• Define and prioritize AI use cases, each with clear inputs, outputs, and a measurable business outcome.
• Build the AI roadmap, including a business case and monetization view for each use case.
• Prototype quickly and test hypotheses with customers before they go onto the roadmap.
• Partner with engineering on the data layer and AI strategy, including the data lake and AI layer, and on the validation work that follows our GA releases.
• Own validation: define success metrics, run pilots, and report results to leadership.
• Write clear, concise use-case and decision docs that engineering, customer success, and sales can act on.
• Work with customer success on pilot design and customer feedback, including our Customer Advisory Board.
• Shape how AI features are packaged and priced, alongside leadership.

Skills, Knowledge and Expertise

• 3–4 years of product management experience.
• Hands-on experience with AI products: you have built with LLMs and shipped or prototyped AI features, not only written about them.
• Comfort prototyping: you can use AI tools, low-code tools, or light code to test an idea yourself and work alongside engineers on one.
• Data fluency: you are comfortable with metrics, experiments, and working from customer data to make decisions.
• Clear written communication, with a bias toward short documents that drive decisions.
• A builder’s mindset: you move fast, learn from real usage, and are comfortable with ambiguity.

Nice to have

• Startup experience, where you owned outcomes across product, design, and engineering.
• Experience in SaaS, CX, survey, or feedback analytics.
• Familiarity with AEC or professional services customers.
• Experience pricing or packaging AI features.