Responsibilities

• Own technical positioning and messaging for the core platform: data unification, entity resolution, AI grounding, integration architecture, and the operational AI layer built on that foundation.
• Demystify the category itself. Build the first-principles content that explains why unifying operational data, resolving entities, and grounding AI are genuinely hard problems, why common approaches fall short, and what an architecture built for this work actually requires.
• Build the technical content library the rest of marketing and sales depends on: technical whitepapers, architecture briefs, security and compliance content, and AI substantiation that holds up under public, legal, and political scrutiny.
• Turn competitive technical intelligence into asymmetric sales tools and teardowns that hold up against horizontal data platforms, operational AI platforms, and AI point solutions.
• Contribute product-led narratives to high-visibility launches, with focus on the technical proof points that make each launch credible.

Requirements

• 5+ years of work experience spanning engineering, management consulting, and product marketing. We expect at least one of these to be a primary anchor, with the others as supporting depth.
• Engineering background, whether through a CS or related degree, an early-career engineering role, or equivalent self-taught depth. You can read a spec, understand a data model, and ask sharp questions about an architectural decision.
• Management consulting experience is a strong plus. The analytical rigor, structured problem decomposition, and ability to learn complex domains fast that consulting builds transfers directly to this role.
• Product marketing experience, ideally in B2B SaaS, AI, or data infrastructure. You have shipped messaging, sales assets, or technical content that moved a real buyer.
• Exceptional writing. You can produce technical content that holds up to a technical reader and translates cleanly for a non-technical one.
• Comfort moving between deep technical conversations with engineers and business outcome conversations with executives, without losing either audience.