About this role
The Content Systems Engineer, Technical Documentation, works on the systems that manage the documentation for Glean's connectors. These connectors are essential integrations that allow Glean to securely access knowledge across customer systems. The core responsibility involves building scalable systems to ensure this technical documentation remains complete and accurate, especially given the rapidly evolving nature of the product. This role exists to bridge traditional technical writing with advanced AI practices to automate and maintain documentation quality at scale. The engineer will focus on creating deterministic automation and agentic workflows to reduce manual effort while maintaining high standards of accuracy and trust.
This position requires a blend of technical writing skills, programming ability, information architecture knowledge, and experience with AI systems. The individual will use AI to analyze complex inputs, generate and transform content, and establish the necessary guardrails to ensure the output is useful and trustworthy for technical administrators. They will be responsible for owning the entire quality lifecycle of the connector documentation, from creation to maintenance. This work directly impacts the customer experience by ensuring technical administrators have reliable information for configuring and troubleshooting integrations.
This role is ideal for someone who enjoys building systems, applying AI to complex information challenges, and taking ownership of a critical product area. A successful candidate will possess the judgment and technical understanding necessary to define evaluation systems and improve the underlying AI processes. They will collaborate cross-functionally to understand product behavior and drive improvements across the entire documentation practice.
What you will do
- Own the end-to-end quality, organization, and maintenance of Glean’s connector documentation.
- Develop scripts, agents, and content pipelines to automate the creation, transformation, validation, and maintenance of documentation.
- Design reusable AI workflows that integrate appropriate models, product context, instructions, and human review.
- Create evaluations and guardrails to manage AI-generated and AI-maintained documentation quality.
- Build deterministic checks to detect documentation that is stale, inconsistent, incomplete, or inaccurate.
- Establish an information architecture to help technical administrators navigate complex setup and configuration flows.
- Partner with various teams to understand product behavior, identify documentation risks, and prioritize improvements.
What you need
- Proficiency in technical writing is required to handle complex technical documentation.
- Experience in programming is necessary to build necessary scripts and automation tools.
- A deep understanding of information architecture principles is needed to structure complex documentation.
- Experience with advanced AI practices is crucial for analyzing inputs and generating content.
- The candidate must be able to build and maintain automated workflows.
- Demonstrated ability to define evaluation systems and guardrails for AI outputs.
- Experience in the connector domain, including configuration, authentication, and deployment, is beneficial.
Nice to have
- Experience with LLM integration
- Experience with information architecture design
Benefits
- Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025)
- Recognized by CNBC’s Disruptor 50
- Recognized by Bloomberg’s AI Startups to Watch (2026)
- Recognized by Forbes AI 50
- Recognized by Gartner’s Tech Innovators in Agentic AI
Skills and tech stack
Questions candidates ask
What is the remote policy?
The posting does not specify the remote work policy.
What is the compensation like?
The posting does not provide specific salary details for this role.
What is the primary technology stack used?
The role involves building workflows using AI models, LLMs, scripts, and agents.
How is the team structured?
The role requires partnering with Engineering, Product, QA, Support, field teams, and customers.