AI Adoption Manager - New York

Automattic Careers•New York City, NY

10d•$150,000 - $230,000•Onsite

About The Position

Help 1,500 people at Automattic use AI tools exceptionally well. Not just “here’s how to use Claude”, but “here’s how to build custom agents for your workflow,” “here’s how to debug when Cursor gets stuck,” “here’s the skill I wrote that solves this exact problem you’re facing.” This is developer advocacy turned inward. You’re embedded with Automattic's engineers, designers, and product teams, helping them level up their AI capabilities through hands-on teaching, tool development, and deep technical expertise. You’re technically experienced enough to build solutions yourself (scripts, agent skills, integrations, demos), but your superpower is translating that knowledge into practical help for others. You might also be an experienced software engineer with a passion for and experience in enabling others around you. You’ll work in-person with our NYC AI team while supporting enablement efforts globally across Automattic’s distributed organization. Why This Role Matters Most companies treat AI adoption as “buy a license, send an email, hope people figure it out.” That doesn’t work. Tools are powerful but rough. Workflows are unclear. People get stuck and give up. You’ll ensure Automattic doesn’t waste the AI opportunity. Help engineers write better code faster, designers prototype ideas more efficiently, support teams resolve tickets more effectively, product teams make better decisions. Your leverage will be enormous: helping 1,500 people work 10% better compounds incredibly.

Requirements

3-5+ years as a software engineer, developer advocate, or similar technical role.
You’ve shipped code and helped others ship code.
Are proficient in at least one programming language (Python, JavaScript/TypeScript, PHP, or similar).
You can build working demos and tools.
Live deep in the AI tools ecosystem. Beyond Claude, Cursor, and ChatGPT, you know the niche players, e.g. n8n for automation, specialized agents, emerging platforms most people haven’t heard of yet. You can recommend the right tool for any given scenario, not just the obvious ones.
Excel at teaching and communication. Comfortable running workshops, creating documentation, and helping people one-on-one. Can translate technical concepts for diverse audiences, from engineers to designers to PMs.
Get more satisfaction from teaching than building alone. You’re energized by the “aha!”moment and want your impact multiplied through helping others.
Experience building with LLM APIs (OpenAI, Anthropic, etc.) and understanding prompt engineering, RAG, and applied AI techniques.
Previous software engineering, developer relations, developer advocacy, or technical education experience.
Track record creating technical content: blog posts, video tutorials, conference talks, or documentation.
Open source contributions or community building experience.
Understanding of multiple programming languages and development workflows.

Nice To Haves

WordPress or PHP experience.
Experience building internal tools or developer productivity solutions.
Background in technical training or curriculum development.
Active presence in developer communities or AI tool ecosystems.
Have a deep software engineering background and care deeply about enabling others.

Responsibilities

Run workshops and training sessions on AI tools (Claude Code, Cursor, emerging platforms); host office hours where people bring real problems and you solve them together.
Build Claude Project skills, custom agents, and scripts that make AI tools more useful for Automattic workflows.
Manage vendor relationships: work directly with AI tool providers to influence roadmaps, secure early access to features, troubleshoot enterprise adoption issues, and coordinate renewals and expansions.
Create practical enablement materials: video tutorials, written guides, example projects, and documentation that engineers and non-engineers can actually use.
Pair program with engineers to teach AI-assisted development workflows; help designers, PMs, and support teams adopt AI effectively.
Drive workflow transformation: identify where teams are stuck in old patterns, design adoption strategies that meet people where they are, turn skeptics into advocates through hands-on problem solving.
Stay deeply current on the AI tool landscape; experiment with emerging capabilities and share what works (and what doesn't).
Coordinate with our AI Enablement, Learn, and DevEx teams on education efforts; build internal community around AI best practices.

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