Manager, Product Operations, AI CTRL

Expedient is a full-stack technology services provider that helps mid-market and enterprise organizations modernize their infrastructure, manage their data, and deploy AI safely at scale. With 25 years in business, a 99 percent client retention rate, a 100 percent uptime SLA, and 200+ active technology certifications, Expedient delivers managed cloud, data, and AI services under a single operating model: Intelligent Infrastructure. 

AI CTRL is Expedient's enterprise AI platform. It is the governed environment through which every prompt, every response, and every automated AI workflow inside a customer's organization is routed, monitored, and controlled. The platform is organized around six pillars: Secure AI Gateway, Multi-Model Chat, Compliance and Observability, AI Data Connectors, Agentic Workflow Engine, and Private Model Hosting. 

About the Role:

The Manager, Product Operations supports the AI CTRL product organization with the reporting, tracking, and operational discipline that scaled product lines depend on. The role pairs with Principal Product Managers and product leadership to maintain a clear view of how the portfolio is performing and where it is headed. 

You will own reporting infrastructure, OKR tracking cadence, order-to-cash inputs, and CPQ inputs for the AI CTRL portfolio. You will deliver a clean, current view of bookings, revenue, costs, partner performance, and customer outcomes that informs the work of product, sales, and finance teams across the organization. 

This role reports to the Senior Director, AI CTRL Product. It is a sales operations function applied to product: builder mindset, automation instinct, and operational rigor. 

What You Will Do:

Performance Reporting and Analytics 

• Build and maintain automated reporting for bookings, revenue, gross margin, consumption, and unit economics across all AI CTRL product lines. 

• Build Retool-based dashboards that replace the manual spreadsheet work product, sales, and finance teams do today. 

• Track and report partner-sourced revenue, partner-attached deal size, certified partner count, and time-to-first-deployed-agent against committed targets. 

• Maintain trial-to-paid conversion, time-to-value, churn, and net retention reporting across pillars. 

• Surface trends, anomalies, and exception patterns to product leadership early, with enough context to act on. 

Order-to-Cash and CPQ Inputs 

• Partner with IT and Sales Operations to maintain CPQ inputs for AI CTRL: product configurations, pricing rules, discount structures, bundle definitions, and approval workflows. 

• Coordinate updates to CPQ when pricing, packaging, or product definitions change, with clear ownership of who signs off on what. 

• Maintain order-to-cash hygiene across quote, provisioning, billing, and renewal stages, in partnership with IT. 

• Track cost components (model costs, infrastructure costs, support costs, partner costs) by product line so the Principal Product Managers can make pricing and packaging decisions on real data. 

OKR Tracking 

• Run the weekly and monthly OKR tracking cadence for the AI CTRL product organization. 

• Prepare OKR status materials, progress narratives, and exception lists for product leadership review. 

• Maintain a defensible source-of-truth view of AI CTRL portfolio performance that the broader organization can reference. 

Cross-Functional Orchestration 

• Serve as the AI CTRL product organization's primary working interface with IT, Finance, Sales Operations, and Customer Success Operations. 

• Translate product needs into clear, actionable specifications for Salesforce, Sigma, billing, and reporting platforms. 

• Coordinate with Sales Operations to align pipeline definitions, stage definitions, and reporting methodology across AI CTRL. 

• Partner with Finance on cost allocation inputs and pricing change implementation. 

Tooling and Automation 

• Build automated reports, alerts, and operational tools using Retool and comparable platforms. Replace manual spreadsheet processes with engineered ones. 

• Maintain the data dictionary for AI CTRL: metric definitions, pillar taxonomy, partner classification, and reporting cadence. 

• Identify operational bottlenecks across the product lifecycle and either automate them or escalate them to IT with a clear specification. 

• Establish data quality discipline so reports across the AI CTRL organization tie to the same numbers. 

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