kapa.ai makes it easy for technical companies to build AI support and onboarding bots for their users. Teams at +150 leading startups and enterprises incl. OpenAI, Mixpanel, Mapbox, Docker, Next.js and Prisma use kapa to level up their developer experience and reduce support.

We enable companies to use their existing technical knowledge sources incl. docs, tutorials, chat logs, and GitHub issues to generate AI bots that answers developer questions automatically. More than 750k developers have access to kapa.ai via website widgets, Slack/Discord bots, API integrations, or via Zendesk.

We’ve been fortunate to be funded by some of the greatest AI investors in Silicon Valley: Initialized Capital (Garry Tan, Alexis Ohanian), Y Combinator, Amjad Masad and Michele Catasta (Replit), and Douwe Kiela (RAG paper author and founder of Contextual AI), and other folks incl. angels at OpenAI.

As an AI Technical Support Engineer at kapa.ai, you'll work directly with our engineering team and customers to ensure successful implementation of our RAG systems. This is an opportunity to be at the intersection of customer success and AI technology, helping developers build better documentation experiences. Check out Docker’s documentation for a live example of what kapa is.

In this role, you will:

• Work closely with customers to troubleshoot and optimize their RAG implementations
• Drive improvements to our onboarding and integration processes
• Debug customer issues across our stack - from vector embeddings to API integrations
• Contribute to our technical documentation and implementation guides

You may be a good fit if you have:

• Strong technical background with hands-on experience building or supporting AI applications
• Deep interest in LLMs and RAG architectures (if you have strong opinions about chunk sizes and embedding models, we want to talk!)
• Strong communication skills - you can are comfortable getting in calls with customers

This is not an exhaustive nor necessary set of attributes. If you're passionate about AI documentation and helping developers succeed, please reach out even if you don't match everything above.

Django, NextJS, and lots of custom retrieval augmented generation pipelining.