Product Operations Leader

At Xplor, we believe that helping people make the most of each day is the most rewarding way to spend ours. We give small and medium-sized businesses cloud-based, intuitive technology solutions that enable them to manage all the hassles of running and growing a business, so business owners can get back to doing what they love. With Xplor Pay, we help businesses get paid quickly and securely – without hidden fees. We built the tech ourselves, and our platform delivers secure, transparent, fast, and accurate payments. We are unified by our purpose of helping people to succeed. So, when you become part of our team, you also become part of the personal connection that strengthens the relationship people have with Xplor products. About the role The Leader of Product Operations builds the operating system that helps Xplor use AI responsibly, adopt it widely, and turn it into revenue and contribution margin, with clear governance and accountability for the results. The role covers three connected areas: AI-enabled productivity, adoption of AI features by our customers, and the commercialization of those features. You will own the shared layer that makes all three work including measurement, value tracking, portfolio governance, intake, cost visibility, and the operating cadence that keeps leaders aligned. Our products and teams span a wide mix of tools and workflow methodologies. You will create a shared layer of measurement, visibility and improvement that works across them, and that product, engineering, go-to-market and executive leaders all trust, and speeds teams up without creating friction. You will report to the Chief AI Officer and partner closely with BU presidents, product and R&D leaders, GTM, Finance, Security, Legal, Privacy and the People team. This is a hands-on leadership role: you will build the function and stay close to the data and the teams. How we work: BUs are central's customers. We measure outcomes, not activity. We decide on a demo, an eval or a metric, not a deck. We keep forums and reporting to the minimum that supports a real decision. What you'll do Own the measurement and board scorecard · Build and run a single scorecard with Finance that records every AI benefit, in one engine, net of AI cost (inference, hosting, tools and support). · Produce the quarterly AI board scorecard covering value and risk measures, with a named owner and source system for every measure. · Run a repeatable prioritization and triage process for operations and tooling improvements, with clear owners, expected impact and follow-up on results. · Turn data into short, decision-ready narratives for the Chief AI Officer and C-suite. Measure AI-enabled productivity · Build a measurement framework that links delivery and AI-SDLC productivity signals (cycle time, throughput, quality, adoption of AI tooling) to business outcomes such as idea-to-customer lead time, PR-to-production rate, change failure rate, escaped defects, rework and capacity moved to customer-facing work. · Help leaders see where AI productivity gains are real, where they are not, and where to invest next. · Act as a neutral orchestrator across teams that use different tools and methodologies (Scrum, Kanban, SAFe-style and hybrids; Jira, Azure DevOps and others), meeting each team where it is. · Find where gains stall before reaching customers (review wait, regression coverage, late QA, launch readiness) and route the fix. · Partner with function owners in support, revenue operations, finance and onboarding to baseline target workflows on fully loaded cost per resolved outcome, with quality held constant. Measure AI product adoption and commercialization · Own the metrics and standardize reporting for how customers adopt and use AI features across the portfolio at 30-60-90 days, from activation and usage depth to retention and satisfaction. · Build the commercial view with Finance and BU leaders: AI and data ARR, paid attach, retention and expansion, win-rate uplift, gross margin per AI feature and cost per successful task. · Run the launch-readiness checklist with BU leaders before any AI price goes live: cost per task known, margin target met after inference, attribution rule and holdout set, sales and customer success enablement ready. Govern Data and AI accountability · Operationalize and maintain decision rights, escalation paths and clear ownership for data and AI initiatives, so every investment has a named accountable owner, success measures, and a review date. · Maintain a portfolio-level register of Data and AI initiatives and risks, and surface issues early to the Chief AI Officer with recommended actions. · Run the Data and AI vendor and partner inventory and monthly review with Procurement, Finance and Security: spend, overlap, security review, data terms and knowledge transfer from consultants. · Track adherence to agreed standards and policies, and report exceptions without becoming a bottleneck for teams. Lead the function · Hire, develop and lead a product operations team, and set its mandate, operating model and success measures. · Apply AI to product operations itself, including automated reporting, insight synthesis and workflow automation. What you'll bring Required · 8+ years in product operations, business operations, strategy and operations, technical program management, product management, or a similar role in a SaaS or technology company, with at least 3 years at a senior or director level. · A track record of building KPI and measurement frameworks that connect product or delivery data to business outcomes such as adoption, retention and revenue. · Experience working with Finance, Sales and Marketing on pricing, packaging, launch or go-to-market performance. · Experience leading cross-functional initiatives across Product, Engineering, Customer Success and executive leadership, and influencing without direct authority, including establishing governance, de