Lead Product Manager – AI Platform

Job Title: Lead Product Manager Reporting To: Vice President – AI Product THE OPPORTUNITY Are you a technical product manager who can connect the dots between how AI works, how it gets used, and how it creates sustainable business value? Tricentis is the industry's #1 Continuous Testing platform, and AI is central to our next phase of growth. We are looking for a Lead Product Manager – AI Platform to own the shared platform layer that powers all AI experiences across the Tricentis portfolio — including our AI Chat product, usage telemetry, and the commercialization model that turns AI capabilities into measurable business outcomes. This role sits at the intersection of product, engineering, and go-to-market. You will ensure that the AI we build is instrumented, packaged, and positioned to win. What You Will Be Doing Own the AI Platform Roadmap: Define and execute the strategy for the shared platform capabilities that underpin all AI features — including AI Chat, credit and entitlement infrastructure, telemetry, and cross-product AI integrations. Lead AI Commercialization: Own how AI capabilities are packaged, metered, and monetized — translating usage data and customer behavior into pricing models that align value delivery with revenue outcomes. Drive Telemetry & Instrumentation: Build the observability layer that makes AI adoption visible — defining the events, metrics, and dashboards that track how customers engage with AI features across the portfolio. Drive Execution: This is a hands-on Lead IC role. You will write detailed technical specs, groom backlogs with engineering, and be directly accountable for platform reliability, adoption, and commercial performance. Responsibilities AI Credits & Entitlement Strategy: Own the design and evolution of our AI credits system — defining metering logic, entitlement tiers, and packaging constructs that scale across customer segments, product lines, and partner programs. Telemetry & Usage Analytics: Define the instrumentation strategy for AI features across the portfolio. You will own the metrics framework that tracks feature adoption, retention, usage concentration, and drop-off — and use those signals to drive product decisions. AI Chat Product Ownership: Own the AI Chat experience end-to-end — from conversation design and context management to integration with underlying AI capabilities and platform APIs. Platform API & Integration Standards: Define the platform contracts and integration patterns that allow individual product teams to build on top of shared AI infrastructure consistently and efficiently. Go-to-Market Alignment: Work closely with product marketing, sales, and customer success to ensure AI capabilities are clearly positioned, properly enablement-ready, and landing value with customers. Responsible AI at Scale: Champion privacy, auditability, and compliance requirements across the platform layer — ensuring enterprise customers can trust and govern how AI is used within their environments. TECHNICAL KNOWLEDGE AI/ML Fluency: Solid understanding of LLMs and AI product architecture — enough to make informed decisions about platform design, API contracts, and capability boundaries without needing to build the models yourself. Telemetry & Analytics Systems: Experience designing event instrumentation and usage analytics pipelines. Familiarity with tools and patterns for tracking product usage at scale. Commercialization & Pricing Mechanics: Understanding of consumption-based pricing models, entitlement systems, and the operational complexity of metering AI usage across a multi-product enterprise portfolio. Platform Thinking: Ability to design shared infrastructure that serves multiple product teams — balancing standardization with flexibility, and short-term delivery with long-term extensibility. Enterprise Security & Compliance: Familiarity with RBAC, audit logging, and data governance as they apply to AI features operating on sensitive enterprise data. What You Need Basic Qualifications (Must Haves) 5–8+ years of Product Management experience, with at least 2+ years in Technical Product Management or AI/Data products. AI/ML Fluency: Demonstrated experience shipping AI-powered products, with an understanding of how LLMs and AI systems behave in production. Commercial Acumen: Experience working on pricing, packaging, or monetization strategy for a software product — ideally in a consumption or usage-based model. Data-Driven Mindset: Strong ability to define KPIs, interpret usage data, and make product decisions grounded in telemetry rather than intuition alone. Enterprise Exper