Technical Writer

zaimlerSan Mateo, CA
167d

About The Position

AI agents can't reason over data they don't understand. Enterprise data today is fragmented across dozens of systems with no shared context, meaning, or structure, and that's why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we're building it. zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives AI agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve. zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa, and Sofus Macskassy (ex-Director of Engineering, LinkedIn), who built one of the largest knowledge graphs in production in the industry at LinkedIn. We're a small, senior team at the seed stage, deploying with major enterprises across insurance, travel, and technology. If you want to build infrastructure that the next decade of AI runs on, we'd love to talk. The Role You'll be zaimler's first technical writer. That means you won't just write docs, you'll decide what the docs strategy looks like, what tooling to use, and how documentation fits into the product and customer experience from day one. Our platform sits at the intersection of knowledge graphs, data infrastructure, and AI agents, and the people using it are senior engineers and data teams at large enterprises. They need documentation that is precise, trustworthy, and written by someone who actually understands the systems behind it. This role touches everything: API references, SDK guides, platform architecture docs, customer onboarding materials, integration guides, and internal engineering documentation. You'll work directly with engineering, product, and GTM to make zaimler's technology accessible and self-serve.

Requirements

  • 5+ years of experience in technical writing, with a focus on developer-facing documentation for infrastructure, data, or platform products
  • A portfolio that demonstrates clear, precise writing for technical audiences (API docs, architecture guides, developer tutorials)
  • Ability to read code and engage directly with engineers about system design, APIs, and data models. You don't need to be a software engineer, but you need to be technically fluent.
  • Experience building documentation programs or information architecture from scratch, not just contributing to existing doc sets
  • Familiarity with docs-as-code workflows (Markdown, Git, static site generators like Docusaurus, MkDocs, or similar)
  • Strong editorial judgment: you know when to write a quickstart vs. a conceptual guide vs. a reference page, and you can make that call without being told

Nice To Haves

  • Experience documenting knowledge graphs, graph databases, semantic layers, or ML/AI systems
  • Background writing for enterprise audiences where accuracy and trust are critical (financial services, healthcare, infrastructure)
  • Experience with developer relations, content strategy, or technical marketing
  • Familiarity with API documentation tools (Swagger/OpenAPI, Redoc, Stoplight)

Responsibilities

  • Own and build zaimler's documentation from the ground up: define the information architecture, select tooling (docs-as-code, CMS, or otherwise), and establish style and quality standards
  • Write and maintain API references, SDK guides, quickstarts, and platform documentation for a technical audience of engineers and data teams
  • Create customer-facing content including implementation guides, solution briefs, and onboarding materials that accelerate enterprise deployments
  • Develop internal documentation such as architecture decision records, runbooks, and engineering onboarding guides
  • Embed with engineering teams to document new features and platform capabilities as they ship, not after
  • Establish a feedback loop with customers and internal teams to identify gaps, improve clarity, and prioritize what to document next
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