Senior Product Manager Remote

Overview

Ada is an AI customer service company whose mission is to make customer service extraordinary for everyone. We're driven to raise a new standard of quality customer service at scale, enabling enterprise companies to deliver experiences that people love–instant, proactive, personalized, and effortless.

Ada is an AI transformation platform and partner—combining strategic expertise with powerful AI agent management technology to accelerate businesses’ AI maturity to keep them ahead of the curve. With Ada, 83% of customer conversations—and counting—are effortlessly resolved through automation, giving teams more time back, companies more resources to focus on growth, and customers more life to focus on what matters most to them.

Established in 2016, Ada is a Canadian company that has powered over 5.5 billion interactions for leading brands like Square, YETI, IPSY, and  , saving millions of hours of human effort. Backed with over $250M in funding from tier-one investors including Accel, Bessemer, First Mark, Spark, and Version One Ventures, Ada is a pioneer in the management and application of AI in customer service.

At Ada, we see growth as a reflection of each individual owner’s personal growth. That’s why our values are rooted in driving progress and continuous improvement. If you’re ambitious and eager to grow, Ada could be the place for you.

At Ada, Product Managers are builders first. They own their work end-to-end, shaping every stage from ideation to market launch. This is a highly visible, high-impact role where you'll define and deliver innovative AI-driven experiences.

Our AI-first development lifecycle changes how we build software. PMs drive what gets built and why- partnering with design to shape the experience and with engineering to ship it. You generate working prototypes to validate ideas before committing to builds. You write specs detailed enough to drive AI agent execution. You use coding agents daily to research, prototype, query data, and move at a pace that would have been impossible a year ago.

• Make AI agent performance transparent and actionable. Define how AI managers at companies like Pinterest, , and Digicel understand what their AI agents are doing, where they're falling short, and what to do about it. The analytics experience is how customers build trust in AI and drive continuous improvement.
• Build, not just manage
  . Use coding agents to prototype and validate ideas with customers early, write detailed specs that drive AI agent execution, and work directly with engineering to ship fast.
• Own product end-to-end. Drive the full lifecycle — from strategy and roadmap through execution, iteration and launch. You are accountable for outcomes, not just output.
• Think in systems, contribute across the product. Analytics is the primary focus, but you won't stay in a lane. The product is built to work as one — you'll see how the pieces connect and step in to make them better.
• Be deeply customer-facing
  . Run discovery with enterprise customers, CX leaders, and end users. Understand how they operate, where AI falls short, and what would make them trust it more. Translate that into product direction.
• Partner tightly with engineering and design. Work shoulder-to-shoulder with the team. Debate architecture tradeoffs, challenge design decisions, and earn trust through competence.
• Measure what matters
  . Set benchmarks, instrument metrics, query the data directly. Relentless focus on whether what shipped actually moved the needle for customers.

• 5+ years in product development (engineering, design, or product management), including 2+ years in a PM role driving products from concept to launch.
• Builder's mindset
  . You prototype before you present. You'd rather show a working concept than a slide deck. You thrive in ambiguity and use rapid iteration to define new product patterns.
• No boundaries. You don't wait for someone else to pull data, prototype an idea, or investigate a technical constraint. You use coding agents, APIs, SQL, and whatever tools get you answers.
• Technically fluent and AI-native. Comfortable with APIs, system architecture, AI/ML concepts, and data…