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Posted Apr 18Product Marketer
at Cognition
San Francisco, United StatesOn-site
Requirements
- WE ARE AN APPLIED AI LAB BUILDING END-TO-END SOFTWARE AGENTS.
- AI agents make it possible to build more software, faster, at higher quality—and Cognition is at the center of that shift.
- We built Devin, the first AI software engineer, and we're working with some of the world's largest enterprises to fundamentally expand what their engineering organizations can deliver.
- Experience in product marketing of technical products - Excellent written and verbal storytelling abilities - Track record of creating compelling content across mediums — customer stories, one-pagers, decks, landing pages -
- Experience creating sales collateral that reps actually use — and a habit of working closely with reps, understanding what they need, and turning around collateral fast - Ability to distill complex technical products into clear, benefit-driven messaging for different personas - Great at building relationships with customers, sales reps, and internal stakeholders and understanding what they need - Genuine curiosity about technical topics and ability to ramp quickly.
- You don't need to write code, but you need to hold your own in conversations with VPs of Engineering, senior developers, and our engineering team.
- - Comfort with rapid iteration: drafting a landing page or one-pager in hours, not weeks - Basic design sensibility (you'll work with designers, but you should be able to mock up or critique a layout) - Highly organized and good at wrangling stakeholders - Desire to work hard - Willingness to travel onsite to customers for shoots, around the US and internationally.
Benefits
- We went from $1M to mid-nine-figures in revenue in a year, and are backed by some of the world’s top investors, including Founders Fund, General Catalyst, Lux Capital, and 8VC. THE ROLE
Additional details
- Software is how the modern world runs—but there's not enough of it, and too much of what exists isn't good enough.
- Banks and governments still run COBOL from the 1970s.
- Budgets go to technical debt and maintenance instead of the features customers actually want.
- The bottleneck has always been the same: engineering talent is scarce and expensive, and budgets only stretch so far.