Skip to content

AI Engineer - ContextHub

Lead development of Context Hub, an open-source CLI for AI agents to access up-to-date API docs. Own technical direction, build infrastructure for intelligent retrieval and community features, requiring 3+ years experience, TypeScript/Node.js proficiency, and strong LLM/AI agent knowledge.

10k – 15kMountain View, CAML EngineeringOnsite3+ YOE

About the role

Responsibilities

  • Own Context Hub end to end: technical direction, growth strategy, and community health.
  • Talk to developers via GitHub issues, user interviews, and usage data to identify features.
  • Invent new ways for AI agents to discover and use knowledge (smarter retrieval, agent-to-agent sharing, self-improving documentation).
  • Build and maintain the Context Hub CLI and core infrastructure for reliability and performance.
  • Design systems for intelligent documentation retrieval, versioning, and curation.
  • Develop features for agents to annotate, enrich, and share knowledge.
  • Collaborate with open-source community: review contributions, triage issues.
  • Experiment with LLM-based approaches to validate, summarize, and improve documentation.
  • Instrument, monitor, and optimize performance and developer experience.
  • Work with Andrew Ng and team on roadmap and technical direction.
  • Collaborate with internal teams for content, processes, and AI-powered solutions.

Requirements

  • Product sense for developer tools; shipped something developers use.
  • Community instincts for open-source.
  • Strong proficiency in TypeScript/JavaScript and Node.js; experience with CLI tools, SDKs, or developer infrastructure.
  • Very strong understanding of LLMs and AI coding agents; built applications integrating language models.
  • Experience with npm package publishing, versioning, open-source maintenance.
  • Strong systems thinking: design APIs, data models, architectures.
  • AI fluency: familiarity with AI-powered coding tools (Claude Code, Codex).
  • Entrepreneurial mindset; self-starter in fast-paced environment.
  • 3+ years professional software engineering experience.

Nice-to-Haves

  • Maintained popular open-source project (1,000+ stars).
  • Background in information retrieval, search, or knowledge graphs.
  • Experience with MCP (Model Context Protocol), tool-use frameworks, agent orchestration.
  • Familiarity with documentation-as-code, static site generators.
  • Graduate degree (Master’s or PhD) in Computer Science, AI, or related.

Skills

TypeScriptJavaScriptNode.jsLLMsAi Coding AgentsNpmCli ToolsInformation RetrievalKnowledge GraphsMcp

Similar roles

ML Engineering jobs

Research Engineer, Domain Scaling

Own end-to-end data strategy and RL environment creation for domain-specific knowledge work (finance, healthcare, legal). Combine applied research with hands-on data sourcing, vendor management, and model performance measurement.

1 – 2San Francisco, CA +1ML EngineeringHybridReward DesignQa Frameworks

Machine Learning Engineer

Build, scale, and maintain complex AI/NLP models for the Verneek AI platform, focusing on production deployment of large-scale systems. Requires 3+ years Python/PyTorch experience and BSc in CS; NLP expertise preferred.

40k – 200kNew York, NYML EngineeringOn-site3+ YOEScalaPython

AI Tutor - Audio Editing

AI Tutor specializing in audio editing trains and refines AI models for voice interactions and sound processing using annotation tools and audio software. Requires exceptional vocal quality, expert audio perception, and proficiency in tools like Pro Tools or Ableton.

62k – 156kUnited StatesML EngineeringRemoteLogicReaper

AI Tutor - Russian

Annotates and curates multilingual audio data, focusing on Russian, to train AI models for voice interactions, speech recognition, and accents. Provides high-quality recordings, transcriptions, and feedback to improve global audio processing capabilities. Requires native Russian proficiency and strong English.

73k – 94kUnited StatesML EngineeringRemoteProsodyPhonetics

AI Tutor - Hungarian

Annotates and curates high-quality multilingual audio data, focusing on Hungarian, to train AI models for voice interactions, speech recognition, and accent handling. Requires native Hungarian proficiency, English B2+, strong auditory skills, and transcription accuracy.

73k – 94kUnited StatesML EngineeringRemoteProsodyPhonetics