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AI is the new electricity. Millions of AI engineers are needed to transform industries with AI, and we’re building the training and tools to support them. Our mission is to empower everyone to build with AI. We have deep connections throughout the AI community, exciting technology, and wonderful teammates, and are seeking a lead engineer to join us on the Context Hub project.
We recently launched Context Hub, an open-source CLI tool that gives AI coding agents the up-to-date API documentation they need—solving the critical problem of agents hallucinating outdated APIs and parameters. Context Hub gained over 10,000 GitHub stars in its first two weeks, making it one of the fastest-growing open-source developer tools in the AI ecosystem. Published as @aisuite/chub on npm and MIT-licensed, the project already has thousands of curated API docs contributed by the community and is growing fast. Additionally, we are evolving Context Hub toward being a Stack Overflow for agents, where agentic feedback on the documentation will be used to help all other agents.
We’re looking for a visiting AI Engineer to join the Context Hub team to lead the next stage of its development. This will shape the future of how AI coding agents gather context, write code, and give feedback that helps the whole community. . You’ll work directly with Andrew Ng and our team on the core product—building features that are used by thousands of developers and their AI coding agents every day.
This is a hands-on engineering role where you’ll design and build infrastructure, improve how agents discover and consume documentation, and help grow Context Hub from a powerful CLI into a comprehensive knowledge sharing platform for AI agents.
If you are who we look for, you are highly GenAI-enabled, leverage AI-powered tools to build and ship quickly, and bring deep curiosity about AI agents and developer tooling, and a passion for open source.
You must already have authorization to work in the United States. This is a contract role with potential for growth.
Here’s what you’ll do
Own Context Hub end to end. You'll be the single-threaded leader for the product — responsible for its technical direction, growth strategy, and community health. You won't be handed a roadmap; you'll create it.
Talk to developers and understand what they need. The best product decisions come from deep empathy with users. You'll engage directly with the developer community — through GitHub issues, user interviews, and usage data — to identify what to build next and why.
Invent new ways for AI agents to discover and use knowledge. Context Hub started as a CLI for fetching docs, but there's enormous room to push further: smarter retrieval, agent-to-agent knowledge sharing, self-improving documentation, private team contexts, and ideas we haven't thought of yet. You'll explore the frontier.
Build and maintain the Context Hub CLI and core infrastructure, ensuring reliability and performance as usage scales across thousands of developers.
Design and implement systems for intelligent documentation retrieval, versioning, and curation so that agents always get the most accurate and relevant context.
Develop features that allow agents to annotate, enrich, and share knowledge across sessions—building toward a self-improving documentation ecosystem (the “Stack Overflow for AI coding agents” vision).
Collaborate with the open-source community to review contributions, triage issues, and maintain a high-quality contributor experience.
Experiment with LLM-based approaches to automatically validate, summarize, and improve documentation quality.
Instrument, monitor, and optimize the tool’s performance and developer experience based on real-world usage patterns.
Work closely with Andrew Ng and the engineering team to define the product roadmap and technical direction for Context Hub.
Collaborate with internal teams to create content, processes, and AI-powered solutions for scalable support of the developer community around Context Hub.
Here are the skills you should have
Product sense for developer tools. You understand what makes developers adopt (and love) a tool. You've shipped something that other developers use — whether it's an open-source project, a CLI, an SDK, or an internal platform — and you made decisions about what to build, not just how to build it.
Community instincts. You know how open-source communities work — what motivates contributors, how to write docs that people actually read, and how to turn users into advocates. You're comfortable being a public face for a project.
Strong proficiency in TypeScript/JavaScript and Node.js, with experience building and shipping CLI tools, developer SDKs, or developer-facing infrastructure.
Very strong understanding of LLMs and AI coding agents—you’ve built applications that integrate with or orchestrate language models, and you stay current with the rapidly evolving AI tooling landscape.
Experience with npm package publishing, versioning, and open-source project maintenance.
Strong systems thinking: you can design APIs, data models, and architectures that are clean, extensible, and well-documented.
AI fluency: Strong conceptual understanding of AI trends and technologies. Familiarity and experience with AI-powered coding tools such as Claude Code, Codex or similar—having built or prototyped software with AI assistance.
Entrepreneurial mindset: Self-starter comfortable working in a fast-paced, small-team environment where you own projects end to end and thrive in ambiguity.
3+ years of professional software engineering experience.
Bonus if you have any of the following
Experience maintaining a popular open-source project (1,000+ stars).
Background in information retrieval, search, or knowledge graph systems.
Experience with MCP (Model Context Protocol), tool-use frameworks, or agent orchestration platforms.
Familiarity with documentation-as-code workflows and static site generators.
Graduate degree (Master’s or PhD) in Computer Science, AI, or a related field.
At DeepLearning.AI, we are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants without regard to race, color, religion, sex, pregnancy (including childbirth, lactation, and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by applicable law. DeepLearning.AI believes that diversity and inclusion among our employees are critical to our success as a company. We seek to recruit, develop, and retain the most talented people from a diverse candidate pool. Selection for employment is decided based on qualifications, merit, and business needs.
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