Director, Product Management (AI Adoption & Enterprise)

Workato•Palo Alto, CA

About The Position

Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business. This role is a strategic and hands-on leadership role responsible for defining and driving the roadmap, vision, and execution for Workato’s AI-first platform experience. This leader will own the end-to-end experience layer that accelerates AI workload growth across the platform — from onboarding and personal workspaces to discovery, modern builder UX, sharing and reuse systems, and marketplace ecosystem expansion. The core mission of this role is to dramatically increase AI adoption across the customer base by redesigning the platform experience so that AI is not a feature — but the primary interface to building, discovering, and operating workflows and agents. This is a transformational role that directly influences developer mindshare, workload expansion, and long-term platform growth.

Requirements

12+ years of Product Management experience, with a strong focus on developer platforms, AI-driven systems, enterprise SaaS, or programmable workflow products.
Minimum 10 years in a senior product leadership role, managing and mentoring high-performing PM teams.
Proven experience driving adoption and growth through UX transformation and platform experience redesign.
Deep understanding of APIs, SDK ecosystems, CI/CD pipelines, version control systems, and workflow-as-code paradigms.
Experience delivering AI-powered product capabilities, including generative interfaces, conversational UX, LLM integrations, or agent-based systems.
Strong familiarity with enterprise governance, identity models, access control frameworks, and scalable architecture principles.
Demonstrated ability to balance rapid innovation with enterprise-grade reliability and compliance.
Track record of shipping high-impact platform capabilities that measurably increased adoption and customer engagement.
Excellent prioritization skills, balancing strategic transformation with near-term delivery commitments.
Experience shaping product narratives in emerging AI-driven enterprise categories is a plus.

Responsibilities

Define and articulate a bold, AI-first product vision that positions Workato as an enterprise AI runtime rather than a traditional automation platform.
Develop a cohesive strategy to increase AI workload adoption through experience transformation — across onboarding, discovery, build, sharing, and marketplace engagement.
Identify structural friction points that slow experimentation or AI usage and design systemic solutions to eliminate them.
Align AI adoption goals with enterprise governance, scalability, and operational excellence standards.
Lead the design and launch of frictionless personal workspaces that enable builders to experiment safely without administrative bottlenecks.
Build AI-driven onboarding flows that convert user intent into working AI-powered workflows within minutes.
Define activation metrics that compress time-to-first-value and accelerate AI workload creation.
Establish clear and secure pathways for promoting assets from sandbox environments into governed production workspaces.
Own the strategy for intent-driven search and intelligent discovery across AI templates, reusable components, agent blueprints, and enterprise patterns.
Design dynamic discovery systems that surface relevant AI capabilities based on user behavior, role, and enterprise context.
Create internal automation galleries and visibility systems that encourage exploration and cross-team AI adoption.
Reduce duplication by enabling structured reuse of AI-powered workflows and standardized patterns.
Define and deliver a next-generation builder experience that embeds AI directly into the workflow creation surface.
Enable live synchronization between visual and code-based representations of workflows.
Enhance debugging, replay, and static analysis tooling to improve developer confidence in AI-generated logic.
Modernize the UX to support agent-based systems, parallel execution, modular design, and AI collaboration.
Ensure the builder experience feels programmable, intelligent, and fast while maintaining usability for diverse personas.
Design forkable workflows with lineage tracking, reusable subflows, version-controlled modules, and structured component libraries.
Enable cross-workspace sharing mechanisms that promote safe and scalable reuse of AI-enabled workflows.
Introduce governance-aware reuse frameworks that balance speed with enterprise control.
Drive measurable increases in reuse rates and cross-team collaboration.
Expand the marketplace to include AI blueprints, agent skills, reusable automation packs, and extensibility frameworks.
Define contribution models, SDK strategies, and governance controls that enable ecosystem growth while maintaining enterprise standards.
Develop rating, certification, and versioning systems that build trust and quality in marketplace contributions.
Drive marketplace adoption metrics tied directly to AI workload growth and ecosystem engagement.
Collaborate closely with Engineering, Design, AI research, Solutions Consulting, Customer Success, Marketing, and Sales to deliver and position AI-first experiences.
Partner with go-to-market teams to shift perception toward AI-native enterprise capabilities.
Ensure cohesive integration of AI experience strategy across adjacent product areas.
Recruit, mentor, and scale a high-performing product management team focused on AI adoption and platform experience transformation.
Foster a culture of experimentation, craftsmanship, accountability, and data-driven decision-making.
Encourage bold innovation while maintaining operational rigor and disciplined execution.