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Developer Relations - Content and Docs

Chalk
CompanyChalk
CategoryUncategorised
LocationSan Francisco
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryUSD 150k–250k
Posted11 Jun 2026
Last verified30 Jul 2026
SourceEmployer career page (ashby)
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Description
About Chalk Chalk is building the data platform that powers the future of machine learning applications. We tear down complexity, latency, and scale barriers that have traditionally constrained ML capabilities. Our platform combines Rust-speed performance with elegant tools that developers love to use. Leading companies depend on Chalk for everything from stopping fraudulent credit card swipes, verifying identities, and maximizing clean energy capture. We've recently raised a $50 million Series A https://www.reuters.com/business/databricks-competitor-chalk-raises-50-million-series-2025-05-28/, led by Felicis. About the Role: We're looking for Chalk's first Content and Docs lead to sit on our Developer Relations team. Docs are the biggest part of this role, but not the whole role. You'll be the person who makes Chalk legible: through documentation, diagrams, educational content, conceptual explainers, and runnable examples that move developers from curious to confident. Increasingly, developers don't read docs alone. They ask Claude, Cursor, and ChatGPT to build with Chalk on their behalf. Our docs are now in the critical path for those agents to succeed. If Claude can't ship working Chalk code, we lose the developer. You'll own that outcome. This is a foundational, cross-functional role. You'll set the strategy, run the publishing system, instrument the feedback loops, and treat docs the way our engineers treat their services: versioned, tested, monitored, and iterated on every week. What You'll Do: - Own and scale Chalk's technical documentation: user guides, SDK and API docs, conceptual overviews, and example workflows. - Translate complex, low-level systems into elegant, accessible writing, reading production code to document with precision and empathy. - Treat docs as a product. Set the roadmap, define what good looks like, and measure it (time-to-first-success, ticket deflection, agent answer quality, GEO and AEO rankings). - Make Chalk's content LLM-native so Claude, Cursor, and ChatGPT can ship correct, current Chalk code on a developer's behalf. Information architecture, retrieval-friendly chunking, canonical examples, llms.txt, and clean versioning. - Design technical diagrams and educational content (tutorials, deep-dives, video scripts, runnable examples) that close the gap between "read about Chalk" and "ship with Chalk." - Build the feedback loop. Mine support tickets, sales calls, and AI search logs for gaps and close them in days, not quarters. - Keep docs living. Every product change ships with docs. Examples are tested in CI. Nothing rots. - Establish Chalk's technical voice and how we communicate as a company. What We're Looking For: - 4+ years in technical writing, developer education, or developer documentation for a technical product. Bonus if you've been the first or only docs hire. - Product instincts. You think in users, jobs, metrics, and roadmaps, not deliverables. - You can read code fluently in Python, Rust, or similar, and reason about it in a repo, not just a CMS. - Comfort designing diagrams and visual explainers. You know when a diagram is doing more work than a paragraph. - Demonstrated experience optimizing content for retrieval, AI search, or LLM consumption. - A portfolio with range: getting-started, deep explainers, reference material, tutorials, diagrams. - High agency. You find the gap and ship. - Comfort with Markdown, static site generators, Git workflows, and CI-tested examples. Bonus Points: - Experience at early-stage startups or with fast-moving product teams. - Contributions to developer platforms or open-source documentation. - Background in developer education, courses, or technical video production. - Familiarity with real-time systems, feature engineering, or inference infrastructure. - Understanding of compiler or query planning concepts. - You've stood up a docs analytics stack (search logs, AI referral tracking, agent eval
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