Content Systems Engineer, Technical Documentation

Role details

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the role Glean is looking for a Content Systems Engineer to own the documentation experience for our connectors—the integrations that allow Glean to securely access knowledge across our customers’ systems. Connector documentation serves technical administrators responsible for configuring access, authentication, permissions, and deployments within their organizations. Keeping this information complete and accurate across a rapidly evolving product requires more than traditional authoring. It requires scalable systems that can detect change, generate and validate content, surface risk, and prevent documentation from drifting away from the product. In this role, you will combine technical-writing expertise with programming, information architecture, and advanced AI practices. You will build deterministic automation and agentic workflows that improve documentation freshness and accuracy while reducing repetitive manual work. You will remain accountable for the quality of the resulting customer experience—not merely for producing content. This is an AI-first documentation role. You will use AI to analyse complex inputs, generate and transform content, identify gaps, and support maintenance at scale. You will provide the judgment, technical understanding, evaluation systems, and guardrails needed to ensure that those systems produce accurate, useful, and trustworthy results. The systems and practices you establish for connector documentation will also help improve quality across Glean’s broader documentation set. You will: Own the end-to-end quality, organization, and maintenance of Glean’s connector documentation. Develop a deep understanding of how Glean’s connectors work, including their configuration, authentication, permissions, deployment, and troubleshooting requirements. Build and maintain scripts, agents, and content pipelines that automate documentation creation, transformation, validation, and maintenance. Design reusable AI workflows that combine appropriate models, tools, product context, instructions, and human review. Create evaluations and guardrails for AI-generated and AI-maintained documentation, investigate failures, and improve the context, tools, prompts, and systems that shape output quality. Build deterministic checks that detect stale, inconsistent, incomplete, or inaccurate documentation. Establish an information architecture that helps technical administrators navigate complex setup and configuration flows. Partner with Engineering, Product, QA, Support, field teams, and customers to understand product behavior, identify documentation risks, and prioritize improvements. Define and track measures of documentation health, including freshness, accuracy, automated-check coverage, manual effort, and field or support complaints. Apply successful tools, standards, and quality systems from the connector domain to the broader Glean documentation practice. About you: Prior professional experience of 8-10 Years creating or maintaining technical documentation for a complex software product. A bachelor’s degree in computer science, technical communication, engineering, or another relevant field. Demonstrated ability to independently build, debug, test, and maintain useful scripts, agents, automations, or content pipelines. Strong proficiency in at least one programming language, preferably Python, TypeScript, or JavaScript. Experience with docs-as-code or software-development workflows, including Git, GitHub, command-line tools, code review, and CI/CD. Advanced practical experience using AI beyond one-off content generation, such as: Strong knowledge of technical-writing and content-design principles, including audience analysis, information architecture, task-oriented documentation, and progressive disclosure. The judgment to organize large amounts of ambiguous or conflicting information without producing unverified or low-quality content. T