Senior Technical Writer - Core Docs - Documentation

What is The Role

We are seeking a Senior Technical Writer to join a team of writers dedicated to our most sophisticated search and AI capabilities! You'll act as a lead contributor and collaborator, bridging the gap between our core engine developers and the global community of data scientists and engineers building the next generation of AI-powered applications.

From vector embeddings to Retrieval-Augmented Generation, you will share stewardship of the narrative for how the world implements Search AI at scale.

Does this sound like the job for you? Check out our docs, tinker with our products, and think about where you fit in! Show us your writing chops and tell us what you can bring to the role. Upload writing samples, or provide links to your portfolio or GitHub contributions.

What You Will Be Doing

• Work within a dedicated docs team to co-own documentation for the latest features, including vector search, NLP tasks, and LLM integrations. You’ll translate raw engineering specifications and under-the-hood mechanics into high-quality tutorials, API references, and conceptual guides that align with team-wide standards.
• Partner with fellow writers to organize complex, multi-layered technical content, ensuring a seamless and logical experience for both beginner developers and expert data scientists. Contribute to our shared Git-based doc workflow, using Markdown and static site generators to maintain a high-velocity documentation pipeline.
• Deep-dive into the product by testing API endpoints, while providing thoughtful, constructive feedback through peer review to ensure our documentation is production-ready.
• Work closely with Engineering, Product Marketing, and Support to deliver a consistent, developer-centric narrative that reflects the voice of the docs team.

What You Bring

• 5+ years in a SaaS or Developer-focused environment writing customer-facing documentation. A deep understanding of the technical writing craft and how to lead content strategy.
• Deep Expertise in Search & AI: A solid grasp of vector embeddings, NLP, and the nuances of integrating Large Language Models into a search stack.
• API Documentation Mastery: Proficiency in documenting RESTful APIs and are comfortable using tools like Postman or cURL to test endpoints and explain complex request/response schemas.
• Technical Proficiency: Can read and understand code snippets in Python (specifically for ML libraries) and JSON (for Elasticsearch queries and ingest pipeline configurations). Understand data structures and how search works—including indexing, mapping, and how vector search differs from traditional keyword search.
• "Docs as Code" Mentality: Proficiency in using Git, GitHub, and Markdown. You thrive in a workflow where documentation is treated with the same care as code.
• Strong Information Architecture Skills: Organization of large, interrelated technical content so it remains scannable and logical for developers at different experience levels and data scientists.
• Collaborative Spirit: Ability to work in a distributed team environment, enjoying the process of peer review and shared ownership to reach a common goal.

Bonus Points

• Experience with Elasticsearch or other vector database technologies.
• Experience contributing to Open Source projects.
• Happy working on the command line and writing basic scripts to automate tasks.

Our docs team helps shape the evolution of our products and services. We care deeply about giving you ownership of what you’re working on. We believe Elastic achieves greatness when you are free to pursue your ideas and are surrounded and challenged by your peers.