E
Exa
Technical Product Marketing (Content)
Skills
Product MarketingData ScienceData AnalysisAI
2 months ago
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Important information
Contract type:
Permanent
Salary:
$150,000 – $250,000 / year
Location:
San Francisco, CA, USA
Work mode:
Onsite
Published on:
12 August 2026
What they need
- We build the search engine for AIs, so we should be the company that best understands how to get found by them. When a developer asks Claude or ChatGPT which search API to use for their agent, the answer should be Exa
- You own organic discovery, and the engine that drives it is a weekly cadence of technical content that engineers respect: benchmarks, teardowns, implementation guides, honest comparisons, and writing about retrieval and agents that could only come from inside this company. Volume matters–ship something good every week
- You will read code, call APIs, run evals, and publish work with your name on it. Answer engine optimization is the strategy layer on top: structuring content so models cite it, covering the entities and questions that matter, and measuring whether we show up in the answers
- This is an AI-first role at an AI-first company. Your research, drafting, and measurement loops should be built with AI, and you should be able to explain what you never let AI touch
- Own a steady publishing cadence of technical content for engineers with a heavy emphasis on video: tutorials, benchmarks, architecture deep dives, comparisons, and release commentary. Success is measured by shipped volume at a quality bar that survives Hacker News, plus organic traffic and signups sourced from it
- Own how Exa appears in AI-generated answers: entity coverage, structured content, citation-worthy source material, and the measurement of citation share across major models and assistants. Success is measured by share of relevant AI answers that cite or recommend Exa
- Own the organic topic map: which questions and keywords we intend to win, the content architecture that supports them, and the internal linking and page strategy behind it. You partner with Digital Marketing who owns site mechanics
- Own the substantive point of view: how retrieval quality is measured and why agents need different search types. Success is measured by the work being cited by developers and by our own sellers
- Own the reporting that connects content to pipeline: organic sessions, signups, AI citation tracking, and which pieces influence deals. Success is measured by leadership trusting these numbers
- Design the workflow that takes an idea to a published, technically accurate piece fast: research, drafting, code examples, fact-checking, and distribution. If a step runs manually more than twice, you should be itching to automate it
- What Success Looks Like:
- Technical content ships every week, and engineers share it without being asked
- We’re growing followers counts on youtube and X
- Exa is cited by major AI assistants when developers ask about search and retrieval for agents
- We win the organic questions that matter to our ICP, and we can show the signups
- Sales and DevRel leverage your content because it is credible
- Benchmarks and comparisons we publish hold up when readers reproduce them
- Content decisions are made from data about what converts- 4+ years writing technical content for developers at an API-first, infrastructure, or developer tools company
- Working knowledge of technical SEO fundamentals and content analytics
- Real developer credibility. You read code, call APIs, run benchmarks, and can build a small demo to make a point. You do not need to have shipped production systems, but engineers should see your work as marketing
- A proven AI builder mindset: you’ve shipped research and writing pipelines using LLMs, and you have judgment about what still requires human touch
- A public portfolio you personally wrote. Show us the piece you are proudest of and be ready to explain the technical claims
- Proven taste in production values for your content
- A working thesis on answer engine optimization, backed by something you have tried and measured
- Experience publishing benchmarks or evals, including handling the criticism that follows
- A background in engineering, data science, or a quantitative field
- Domain depth in search, retrieval, RAG, or agent frameworks
- Multimedia range: video walkthroughs, conference talks, or livestreamed builds
- Experience growing an organic channel from near zero at an early-stage company
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