Senior Staff Product Marketing Manager, AI

Temporal · Enterprise · United States · Product Marketing

This role is for a Senior Staff Product Marketing Manager focused on Temporal's AI initiatives. The person will define positioning and messaging for Temporal in the AI space, translate technical capabilities into value propositions, and drive adoption for AI-native companies, AI labs, and enterprise customers using AI. They will work closely with product, engineering, sales, and marketing to shape strategy and GTM for AI segments.

What you'd actually do

  1. Define and own positioning and messaging for Temporal’s AI use cases across AI-native startups, AI labs, and enterprise customers adopting AI
  2. Develop clear value propositions for how Temporal supports AI workflows, agents, LLM orchestration, human-in-the-loop systems, and long-running AI processes
  3. Lead competitive intelligence related to AI infrastructure, orchestration, workflow engines, and adjacent platforms
  4. Partner with product and engineering to influence roadmap decisions based on market and customer insights
  5. Plan and execute product launches, announcements, and GTM strategies related to AI capabilities and use cases

Skills

Required

  • Senior, strategic product marketer with experience owning end-to-end PMM for complex, technical products
  • Deep familiarity with AI, ML, or data platforms, especially in developer-facing or infrastructure contexts
  • Comfortable marketing to highly technical audiences including developers, platform teams, and architects
  • Able to translate technical concepts into crisp, differentiated messaging without oversimplifying
  • Strong storyteller who can create narratives that resonate with both technical and business stakeholders
  • Proven track record of influencing product direction and GTM strategy at a senior level
  • Highly collaborative, with experience working closely with product, engineering, and sales leadership
  • Self-directed and comfortable operating in ambiguous, fast-moving environments
  • Detail-oriented in execution but able to think at the system and market level
  • Excited by the opportunity to define a category and shape how AI-powered systems are built in production

What the JD emphasized

  • AI infrastructure
  • orchestration
  • workflow engines
  • AI use cases
  • AI workflows
  • agents
  • LLM orchestration
  • human-in-the-loop systems
  • long-running AI processes
  • AI capabilities