Requirements7+ years experience preferredBachelor's degree preferred7+ years of experience in Product Management or Product Owner roles, preferably in enterprise SaaS, Revenue Operations, or B2B commercial platformsDemonstrated experience in AI/ML products from discovery through delivery and adoptionExperience working within Agile/Scrum delivery frameworks with cross-functional engineering and data science teamsFamiliarity with LLM applications, NLP, and generative AI in enterprise workflows is strongly preferredWhat the job involvesDesigns, develops and manages the lifecycle of a product or group of products from concept to launch to end of lifeTranslates market opportunities and customer demand into viable products and services that differentiate Equinix in the marketSets the vision and strategy for their product ensuring it is competitively positioned and customer-centricManages the product roadmap including features, upgrades and maintenance of the product or product lineWorks cross functionally with user experience, engineering, operations, solution architects, marketing and others to design, build and launch new products and/or product featuresProduct Lifecycle ManagementExecutes on the defined strategy and vision for AI within the Quoting, Solutioning, and Contracting domains of Lead to CashManages the full AI product lifecycle — from ideation and discovery through build, launch, adoption, and continuous improvementMaintains awareness of the competitive AI landscape and emerging technologies applicable to CPQ, CLM, and solution design workflowsProduct Strategy, Vision and RoadmapPartners with Sales, Tech Sales, and Sales-supporting teams to translate business needs into clearly scoped, AI-enabled solutionsGathers, documents, and designs the best possible end-user experience across quoting, solutioning, and contracting workflows — incorporating the voice of the customer and the voice of the rep into the AI product roadmapInvolves engineers, designers, data scientists, and business stakeholders to create a shared vision and clear, measurable goals for each AI product initiativeIdentifies and documents where AI reduces friction across the quote-to-contract lifecycle — pricing inconsistency, manual contract redlines, slow approvals, scope estimation errors — and incorporates those opportunities into a prioritized AI roadmapDefines a multi-horizon roadmap that balances quick-win automation with longer-term intelligent decision support across all three domains:Product PerformanceDefines the metrics and KPIs used to measure AI-enabled product success across all three domainsEstablishes baselines and targets for each AI initiative prior to launchMonitors model performance post-launch, defines retraining triggers, and leads product retrospectives tied to outcome dataProduces executive-level reporting on AI initiative ROI, adoption, and delivery progressCross-Functional CollaborationDesigns product training curriculum for AI features across Quoting, Solutioning, and Contracting — ensuring end users understand not just how to use AI tools, but when to trust, override, or elevate AI outputsLeads cross-functional trainings, demos, and working sessions with users and business stakeholdersPartners with data engineering on feature pipelines, training datasets, data quality standards, and model retraining workflowsBacklog PrioritizationCreates and owns the AI product backlog across Quoting, Solutioning, and Contracting — writing clear user stories, acceptance criteria, and definition of done for every AI featureWorks regularly with the team to refine the backlog, add detail, resolve dependencies, and sequence work by business value and technical feasibilityCollaborates closely with engineering and data science to size work, surface risks, and maintain a healthy sprint-ready backlogApplies Lean principles to eliminate process waste before layering AI on top — ensuring AI solves real friction, not just digitizes broken workflowsManages dependencies between AI feature teams and platform, integration, and infrastructure teamsTest Case Definition and UAT CoordinationLeads definition of allowable configurations, test cases and executes UATStakeholder ManagementManages stakeholder expectations within and/or across functionsIdentifies and proactively includes correct stakeholders and communications effectivelyUnderstands stakeholder needs and builds effective relationshipsUtilizes effective methods of communication with stakeholders, varying approach accordingly#J-18808-Ljbffr