Senior Product Manager
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Key skills for this role
About the Role
Equinix is seeking a Senior Product Manager to lead AI product lifecycle within the Quoting, Solutioning, and Contracting domains of Lead to Cash. You will define strategy, manage roadmap, and collaborate with cross-functional teams to deliver AI-enabled solutions.
Key Skills for This Role
Responsibilities
- Execute on the defined strategy and vision for AI within the Quoting, Solutioning, and Contracting domains of Lead to Cash.
- Manage the full AI product lifecycle — from ideation and discovery through build, launch, adoption, and continuous improvement.
- Maintain awareness of the competitive AI landscape and emerging technologies applicable to CPQ, CLM, and solution design workflows.
- Partner with Sales, Tech Sales, and Sales supporting teams to translate business needs into clearly scoped, AI enabled solutions.
- Gather, document, and design the best possible end user experience across quoting, solutioning, and contracting workflows.
- Define metrics and KPIs to measure AI enabled product success; establish baselines and targets; monitor model performance post launch.
- Create and own the AI product backlog across Quoting, Solutioning, and Contracting — writing clear user stories, acceptance criteria, and definition of done.
- Lead definition of allowable configurations, test cases and execute UAT.
Requirements
- 7+ years of experience in Product Management or Product Owner roles, preferably in enterprise SaaS, Revenue Operations, or B2B commercial platforms
- Demonstrated experience in AI/ML products from discovery through delivery and adoption
- Experience working within Agile/Scrum delivery frameworks with cross functional engineering and data science teams
- Familiarity with LLM applications, NLP, and generative AI in enterprise workflows is strongly preferred
- Bachelor's degree preferred
Full Job Posting
Job Summary
- Designs, develops and manages the lifecycle of a product or group of products from concept to launch to end of life. Translates market opportunities and customer demand into viable products and services that differentiate Equinix in the market. Sets the vision and strategy for their product ensuring
Product Lifecycle Management
- Executes on the defined strategy and vision for AI within the Quoting, Solutioning, and Contracting domains of Lead to Cash
- Manages the full AI product lifecycle — from ideation and discovery through build, launch, adoption, and continuous improvement
- Maintains awareness of the competitive AI landscape and emerging technologies applicable to CPQ, CLM, and solution design workflows
Product Strategy, Vision and Roadmap
- Partners with Sales, Tech Sales, and Sales supporting teams to translate business needs into clearly scoped, AI enabled solutions
- Gathers, 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 roadmap
- Involves engineers, designers, data scientists, and business stakeholders to create a shared vision and clear, measurable goals for each AI product initiative
- Identifies 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 roadmap
- Defines a multi horizon roadmap that balances quick win automation with longer term intelligent decision support across all three domains
Product Performance
- Defines the metrics and KPIs used to measure AI enabled product success across all three domains
- Establishes baselines and targets for each AI initiative prior to launch
- Monitors model performance post launch, defines retraining triggers, and leads product retrospectives tied to outcome data
- Produces executive level reporting on AI initiative ROI, adoption, and delivery progress
Cross Functional Collaboration
- Designs 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 escalate AI outputs
- Leads cross functional trainings, demos, and working sessions with users and business stakeholders
- Partners with data engineering on feature pipelines, training datasets, data quality standards, and model retraining workflows
Backlog Prioritization
- Creates and owns the AI product backlog across Quoting, Solutioning, and Contracting — writing clear user stories, acceptance criteria, and definition of done for every AI feature
- Works regularly with the team to refine the backlog, add detail, resolve dependencies, and sequence work by business value and technical feasibility
- Collaborates closely with engineering and data science to size work, surface risks, and maintain a healthy sprint ready backlog
- Applies Lean principles to eliminate process waste before layering AI on top — ensuring AI solves real friction, not just digitizes broken workflows
- Manages dependencies between AI feature teams and platform, integration, and infrastructure teams
Test Case Definition and UAT Coordination
- Leads definition of allowable configurations, test cases and executes UAT
Stakeholder Management
- Manages stakeholder expectations within and/or across functions
- Identifies and proactively includes correct stakeholders and communications effectively
- Understands stakeholder needs and builds effective relationships
- Utilizes effective methods of communication with stakeholders, varying approach accordingly
Qualifications
- 7+ years experience preferred
- Bachelor's degree preferred
- 7+ years of experience in Product Management or Product Owner roles, preferably in enterprise SaaS, Revenue Operations, or B2B commercial platforms
- Demonstrated experience in AI/ML products from discovery through delivery and adoption
- Experience working within Agile/Scrum delivery frameworks with cross functional engineering and data science teams
- Familiarity with LLM applications, NLP, and generative AI in enterprise workflows is strongly preferred
Pay Range
- Canada Toronto Office TRO : 131,000 181,000 CAD / Annual
- United States Dallas Infomart Office DAI : 136,000 204,000 USD / Annual
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