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Rubrik is seeking a visionary Senior Director of Product Management to lead the AI-driven transformation of its Go-To-Market (GTM) and Customer Experience (CX) platforms. This is a hands-on leadership role combining architect and player-coach responsibilities, with end-to-end accountability for product vision, agentic system design, and delivery of intelligent experiences across the revenue lifecycle—from prospect through quote, cash, renewal, and support.
You will own the multi-year product roadmap for embedding advanced AI across the entire GTM and CX stack, translating corporate strategy into a rigorously prioritized portfolio of AI initiatives grounded in measurable business impact. The role demands deep domain mastery of Quote-to-Cash (Q2C), partner motions, post-sale onboarding, and support workflows, using that expertise as the source of truth for every design decision.
Key responsibilities include redesigning processes from first principles before introducing tooling or agents; re-imagining Q2C and New Product Introduction (NPI) as clean, measurable flows; instrumenting every process for visibility into cycle time, productivity, and value delivery; defining data contracts and master-data alignment across Salesforce, CPQ, ERP/billing, and CX systems; and advancing the organization from AI-first posture to true agentification—business processes operating as governed, multi-agent systems with human-in-the-loop control.
You will bring an architect-first, systems-designer mindset, shaping scalable AI architectures for GTM/CX workflows leveraging LLMs, agentic frameworks, vector search, orchestration layers, and real-time inference in close partnership with Engineering. You'll prototype, validate, and iterate on high-impact AI concepts through rapid proof-of-concept work, owning the product side of the full AI software development lifecycle. The role includes leading, mentoring, and scaling a high-performing team of AI-fluent product managers while maintaining platform health by balancing innovation velocity with stability, scalability, and technical-debt reduction.
Success requires raising the bar on craft: data-driven decisions, experimentation frameworks, and business-value quantification over vanity proofs-of-concept. You will set the standard for production-grade AI with eval coverage, human-in-the-loop guardrails, and responsible-AI practices baked into the definition of done.
