Who We Are

AI coding is the largest use case of enterprise AI adoption today, as is evident from the success of Anthropic on Claude Code, Cursor’s $60B exit to SpaceX, and Cognition’s $48B valuation.

The bottleneck now has moved from code generation to security and safety - AI agents write code faster than any team can review it, and over 65% of the lines of code produced by them are insecure. Vulnerabilities are piling up 16x faster than companies can fix them, and adversaries are able to exploit these new vulnerabilities within hours.

AURI by Endor Labs closes that gap. It runs inside the harness where coding agents work, through hooks, skills and MCP, so the controls sit outside the model and every agent action is visible. Underneath is our patented code context graph, which maps code, open source, containers and infrastructure. It shows which vulnerabilities can actually be reached and exploited, then delivers fixes that won’t break the application. Security teams get evidence instead of noise, and developers get fixes instead of tickets.

The companies building AI trust us to secure it - our customers include OpenAI, SpaceX, DoorDash, Dropbox, Atlassian, MongoDB, Snowflake, Robinhood and Peloton to name a few.

Endor Labs is the third company from Founder & CEO Varun Badhwar, who built Prisma Cloud, the platform that helped define cloud security, from $0 to $300M ARR at Palo Alto Networks. We’ve raised $163M from Lightspeed, Coatue, DFJ Growth, Salesforce Ventures and Dell Technologies Capital.

Software runs everything around our lives today - banking, hospitals, airports and power grids. AI now writes more of it every day, and our mission is to make sure the world can trust that software. Come build that future with us.

How You'll Make an Impact

Execute Endor Labs' Answer Engine Optimization (AEO) strategy by building and maintaining a consistent pipeline of high-quality technical content.
Create how-to guides, integration walkthroughs, technical explainers, FAQs, glossaries, and comparison pages across application security, AI code security, software supply chain security, and DevOps.
Develop content covering technical topics such as CI/CD, Kubernetes, containers, infrastructure-as-code, and AI coding agents.
Apply AEO best practices across all content, including answer-first writing, question-led headings, concise explanations, structured tables, lists, schema markup, and semantic HTML.
Refresh and optimize existing blogs, documentation, and website content to improve visibility and relevance across AI-powered answer engines and traditional search.
Build repeatable content workflows, templates, and briefs using AI writing tools to improve content production and scale output without compromising quality.
Validate technical content by testing code snippets, configuration examples, and CLI commands, and verifying technical claims with product documentation and engineering teams.
Collaborate with Product Marketing, Engineering, and Digital teams to ensure technical accuracy, consistency, and alignment with content priorities.
Own the editorial quality of content produced by internal teams, freelancers, and AI tools, ensuring clarity, accuracy, consistent terminology, and AEO readiness.
Track content output, publishing timelines, and AI visibility metrics, including citation share and answer accuracy for target prompts.
Share insights and performance learnings with the marketing team to continuously improve the AEO strategy and content approach.

What You Bring to the Table

If you enjoy working at the intersection of technical content, developer education, and AI-powered search, and the requirements below match your background, we'd love to hear from you!

5+ years of experience in technical writing and editing, preferably for developer, DevOps, application security, or infrastructure audiences.
Strong understanding of DevOps concepts and hands-on familiarity with CI/CD pipelines, containers, Kubernetes, and Infrastructure as Code (IaC).
Ability to build and test sample CI/CD pipelines to validate technical workflows and examples before publishing.