Director of Product Marketing

Responsibilities

• What you'll do
• - Own positioning and messaging
• - Define positioning, value propositions, and messaging frameworks for the mpathic platform and our expert-led services across our core audiences: frontier AI labs, large enterprises building and deploying AI, and Life Sciences organizations.
• - Develop buyer personas, ideal customer profiles, and use cases in partnership with Sales and Customer Success.
• - Maintain competitive and market intelligence, including battlecards that help sellers handle the questions they actually hear.
• - Translate complex ideas in behavioral science, evaluation, and AI safety into clear, credible language for technical, clinical, and executive buyers.
• Lead sales enablement
• - Build and maintain the sales playbook: discovery guides, qualification frameworks, objection handling, pitch and demo narratives, pricing and packaging guidance, and sales-facing one-pagers and decks.
• - Design and run seller onboarding and ongoing training, including product and market updates, so new and tenured sellers can tell the mpathic story consistently.
• - Own the enablement calendar, content repository, and tools, and keep sales materials current and easy to find.

Requirements

• Have [8+] years of experience in product marketing, sales enablement, or related go-to-market roles at a B2B software, AI/ML, or hybrid software-and-services company, including leadership experience.
• Have built positioning and messaging for technical and complex products and sold into enterprise buyers.
• Have owned a sales enablement function or program and can show how you measured its impact.
• Can translate technical, scientific, or clinical concepts into clear value for different audiences.
• Work collaboratively across Sales, Product, Customer Success, and Marketing, and respect clear ownership lines with peers.
• Are comfortable with ambiguity in an early-stage, remote-first environment and happy to be both strategic and hands-on.
• Have experience in AI safety, AI/ML infrastructure, healthcare, or life sciences, or are excited to develop it. Familiarity with evaluation, red teaming, or benchmarking concepts is a plus.