About The Position

Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility. Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today’s fast-changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com. Why join us? Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. If this sounds right up your alley, please submit an application. We look forward to getting to know you! Also, feel free to check out why: Business Insider named us an “enterprise startup to bet your career on” Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America Quartz ranked us the #1 best company for remote workers Responsibilities AgentX Support is Workato’s flagship AI-native engine designed to transform customer service from a cost center into a strategic advantage. The platform enables AI agents to reason through complex customer issues, orchestrate backend actions across enterprise systems, and provide real-time, high-fidelity guidance to human support agents during live chats, voice calls, and video interactions. The result is faster resolution, lower operational costs, and improved customer satisfaction at scale. We are seeking an exceptional Principal Product Manager to lead AgentX Support from proven market traction to category leadership. The customer service industry is undergoing a fundamental platform transition driven by advances in AI and increasing enterprise demand for automation, efficiency, and quality. The global market for AI in customer service is projected to exceed $30B by 2030, with enterprises actively seeking AI-first alternatives to legacy help-desk platforms. AgentX Support is already proven in high-volume B2C and e-commerce environments, delivering material improvements in resolution time, customer satisfaction, and productivity for human support teams. AgentX Support is a strategic investment area within Workato, backed by significant committed capital and engineering resources, with a clear trajectory toward a $100M+ product line. As Principal Product Manager, you will play a defining role in shaping how Workato captures this opportunity and scales AgentX Support to serve millions of end users and thousands of enterprise support teams. This role offers the opportunity to define and scale a new category in AI-powered customer service. This is a senior, high-impact product leadership role for an experienced product manager operating at the intersection of AI capability, platform architecture, and business outcomes. You will report to VP, Product Management, AI Apps and partner closely with senior leaders across Product, Engineering, AI Research, Design, and Go-To-Market functions. You will own the vision, roadmap, and execution of AgentX Support as it evolves from a successful vertical solution into a multi-industry enterprise platform. In this role, you will also be responsible to:

Requirements

  • 10+ years of product management experience in enterprise software
  • Demonstrated success building 0-to-1 products or defining new market categories
  • Track record shipping ML/AI products to production (not just prototyping)
  • Experience with customer support platforms or CRM systems
  • Experience with real-time systems or high-throughput environments.
  • Strong systems thinking and comfort designing across APIs, data, models, and workflows
  • Sufficient technical depth to partner effectively with engineering and AI research teams
  • Ability to operate effectively in ambiguous, fast-moving environments
  • Exceptional written and verbal communication skills, with executive-level presence

Nice To Haves

  • Familiarity with AI agent frameworks, tool invocation, policy engines, and AI safety patterns
  • Experience building products for frontline operational users, including human support agents
  • Evidence of industry thought leadership through speaking, writing, or advisory roles
  • MBA or advanced degree in a relevant field

Responsibilities

  • Category Definition and Product Strategy
  • Define the vision and long-term strategy for AI-native, agentic customer support
  • Establish the product narrative and positioning that differentiates Workato in the customer service market
  • Represent Workato’s point of view with customers, partners, and industry stakeholders
  • Partner with design and marketing to translate product capabilities into clear customer value
  • AI Agent Resolution and Orchestration
  • Define how AI agents interpret intent, reason through complex customer issues, and determine when to act autonomously
  • Design orchestration frameworks that connect large language models with enterprise systems of record
  • Lead the development of workflows that enable AI agents to execute actions such as refunds, order modifications, and escalations
  • Ensure appropriate controls for safety, observability, compliance, and human-in-the-loop oversight at enterprise scale
  • Human Support Agent Experience
  • Define the next-generation support agent workspace augmented by real-time AI guidance
  • Deliver systems that surface relevant context, recommendations, and next-best actions to human support agents during live customer interactions
  • Optimize collaboration between AI agents and human support agents without increasing operational complexity
  • Drive measurable improvements in human support agent efficiency, accuracy, and satisfaction
  • Multi-Modal Customer Engagement
  • Define and deliver new modes of customer support beyond chat and email, including voice and video interactions
  • Own the product strategy for AI-powered voice and video experiences, including real-time transcription, intent understanding, reasoning, and action execution
  • Ensure consistent agentic resolution capabilities across text, voice, and video channels
  • Design seamless handoffs between AI agents and human support agents in live, real-time interactions
  • Product Analytics, AI Quality, and Continuous Improvement
  • Define the product analytics strategy for AgentX Support, including metrics, dashboards, and insights that measure resolution quality, efficiency, and customer outcomes
  • Establish frameworks to measure, infer, and track the effectiveness, correctness, and reliability of AI agent responses
  • Deliver visibility into AI agent performance, including accuracy, grounding, confidence, policy adherence, and escalation behavior
  • Enable customers to understand, audit, and continuously improve AI-driven resolutions using analytics, insights, and recommendations
  • Partner with engineering, data, and AI teams to build evaluation pipelines, feedback loops, and continuous optimization mechanisms
  • Use product data and AI quality signals to inform roadmap priorities, model iteration, and business decisions
  • Product Execution and Delivery
  • Own the end-to-end product roadmap from early innovation through platform-scale execution
  • Partner closely with Engineering and AI teams to deliver reliable, production-grade systems
  • Collaborate with Product Marketing, Sales, and Customer Success to achieve product-market fit and adoption
  • Define success metrics including resolution rate, time to resolution, CSAT, containment, and business impact
  • Drive continuous improvement through experimentation, data analysis, and customer feedback
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