About the job
As a Product Portfolio Operations Manager-Intelligence & AI within Product Portfolio Operations, you serve as the quantitative foundation for portfolio decision-making, building and maintaining insights measurement infrastructure, AI-powered tooling, and a customer signal aggregation layer. You serve as the quantitative foundation for portfolio decision-making, building and maintaining insights measurement infrastructure, AI-powered tooling, and customer signal aggregation layer. This role operates under a clear principle: Product Portfolio Operations enables, facilitates, and governs - it does not own or direct product outcomes. You will balance four operating modes: building and maintaining the portfolio's measurement backbone, detecting and surfacing anomalies and signals before they become blind spots, governing data quality and metric standardization, and architecting AI-powered systems and agentic workflows that serve as a force multiplier across Product Portfolio Operations function.
Responsibilities
Design insights framework and data architecture in partnership with key stakeholders, spanning product metrics, delivery metrics, financial metrics, adoption metrics, and flow metrics across all platform products, ensuring traceability from dashboard to source system
Build and maintain portfolio dashboards at three altitude levels - executive, operational, and team-level - ensuring leaders and product teams can act on what they see without interpretation overhead
Identify and automate repetitive product portfolio operations tasks including status collection, metric aggregation, report generation, and intake triage scoring, delivering measurable reduction in manual operational overhead each quarter
Proactively surface cross-product insights and portfolio-level patterns such as adoption anomalies, delivery velocity trends, cost-per-feature shifts, and dependency bottleneck patterns to relevant product teams and Product Portfolio Operations leads
Build and maintain a unified portfolio-level view of customer signals by synthesizing product-team-sourced data into cross-product patterns and portfolio-level customer health indicators, with defined data-sharing contracts between product teams and PPO
Own the portfolio-level adoption and consumption measurement infrastructure including data pipelines, dashboards, and cross-product benchmarking for active users, feature adoption curves, onboarding completion rates, time-to-value, and churn/re-engagement signals
Design, build, and maintain agentic AI systems that connect portfolio tools into intelligent, continuous pipelines - including AI-powered anomaly detection, auto-generated Portfolio Intelligence Briefs, natural language querying for portfolio data
Qualifications
Minimum
5+ years of experience or equivalent expertise in data architecture, portfolio analytics, business intelligence, or product engineering within technology organizations
Demonstrated ability to design and maintain enterprise-grade insights models, dashboards, and automated data pipelines across multiple products or platforms
Strong experience with metric definition, data governance, and data quality management - contributing to a single source of truth across complex product ecosystems
Proven ability to translate data into actionable insights across horizontal and vertical audiences
Experience operating within product development lifecycles and agile methodologies at a portfolio or multi-product level
Preferred
Experience designing or implementing AI-powered automation, agentic workflows, or intelligent data pipelines in an enterprise environment
Familiarity with flow metrics (lead time, cycle time, throughput, WIP) and their application to portfolio health monitoring
Experience with product-level insights, analytics frameworks, and outcome measurement methodologies
Background in developer platforms, platform engineering, or internal product ecosystems with adoption telemetry and consumption analytics
Strong stakeholder management skills with the ability to interface with executive leadership, functional leads, product teams, and engineering teams across a multi-product portfolio