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DeepLearning.AI is an education technology company that is revolutionizing the global workforce by empowering individuals to shape an AI-powered future. With a focus on world-class education, hands-on training, and a collaborative community, DeepLearning.AI offers a range of products and services to support individuals in their AI journey. Through their extensive course offerings on Coursera, DeepLearning.AI provides world-class education to help expand technical knowledge. They also offer hands-on training to equip learners with practical skills and foster a collaborative community of peers and mentors. Founded in 2017 by Andrew Ng, a renowned machine learning and education pioneer, DeepLearning.AI has quickly become a leading platform for AI education. Their high-quality programs have gained a global following, making them a pathway for individuals aspiring to build a career in AI. In addition to their own offerings, DeepLearning.AI is part of a larger ecosystem of companies working towards an AI-powered future through education, business, and more. Whether you're just starting or already an ML practitioner, DeepLearning.AI has the resources and support to help you succeed.

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## Visiting Engineer - ContextHub

**Location:** Mountain View, CA

**Employment Type:** Contract to hire

**Work Arrangement:** On-site

**Compensation:** $10,000 - $15,000 a month

### Overview

You'll be the single-threaded leader for Context Hub, an open-source CLI tool that gives AI coding agents up-to-date API documentation. 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. You'll work directly with Andrew Ng and the team on the core product—building features used by thousands of developers and their AI coding agents every day.

### Key Responsibilities

- 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.

### Required Skills & Qualifications

- 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.

- Must have authorization to work in the United States.

### Preferred Skills & Experience

- 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.

career - Visiting Engineer - ContextHub

Interim

A Rust Crate/CLI for CPU inference of LLMs

Powerful collaboration, review, and code management for open source and private development projects

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AI Agents

A superset of JavaScript that compiles to clean JavaScript output

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Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.

Node.js

Lead AI Engineer

Product Engineer

Developer Relations

The role involves leading the development of Context Hub, an open-source CLI tool for AI coding agents, with responsibilities including designing infrastructure, engaging with the developer community, and collaborating with the team on product direction.

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