Danswer is the open source AI Assistant connected to your company's docs, apps, and people. We sync to all sources of information (Slack, Google Drive, Confluence, Github, etc.) and provide a single place where users can ask anything and get an answer immediately. Think your most knowledgeable co-workers, all-rolled into one, and available 24/7!

We also allow users to create custom assistants with access to specific knowledge and tools. For example, customer support teams have built out agents to auto-answer inquiries based on specific internal knowledge sets. Sales teams have created an assistant who they can chat with about their past sales calls, find patterns, and use this information to close more deals. The possibilities are endless 🤯

💻 About the company

Danswer is the open source AI Assistant connected to your company's docs, apps, and people. We sync to all sources of information (Slack, Google Drive, Confluence, Github, etc.) and provide a single place where users can ask anything and get an answer immediately. Think your most knowledgeable co-workers, all-rolled into one, and available 24/7!

We also allow users to create custom assistants with access to specific knowledge and tools. For example, customer support teams have built out agents to auto-answer inquiries based on specific internal knowledge sets. Sales teams have created an assistant who they can chat with about their past sales calls, find patterns, and use this information to close more deals. The possibilities are endless 🤯

🤝🏻 About the founders

Yuhong Sun - Expertise in Machine Learning (with specialization in NLP) as well as backend systems. Previously working on Deep Learning for NL-to-SQL and Semantic Search at Alation, inc.

Chris Weaver - Previously TL on the anti-fraud engine team at Robinhood. In a past life, I was a top 100 League of Legends / Hearthstone player 😎

💡 About the role

As a founding engineer hire, you'll play a pivotal role in shaping the core product. Help us become the single application where users go to find all work related information. This is an in-person role based in San Francisco, CA.

• Building a consumer grade UI experience for our GenAI Chat, Enterprise Search, and Admin/Curation features
• Improving the flexibility and quality of the search pipeline, building a semantic understanding of customer organizations, extending the current permission/access controls, and expanding the knowledge curation features
• Own the entire development cycle of new features, from conception to production
• Collaborate with founders to shape and influence the direction of the product and contribute to the engineering strategy

🚀 You’ll be successful in this role if you…

• Have 1-5 years (or more) of software engineering experience building real-world applications
• Experience with Typescript/React/NextJS, Python, Relational DB (Postgres)
• Experience working in a fast moving startup and in small teams with minimal guidance
• Excellent communication skills, with a strong ability to collaborate with others (both teammates and external customers)

⭐ Bonus points

• Experience with Docker/Kubernetes, cloud technologies (AWS, GCP, Azure), and on-prem/cloud deployments
• Experience (or even just interest) in information retrieval and AI (NLP, Deep Learning, GenAI)
• Previous Founder or 0-to-1 engineer at early startup

💪 Challenges we're solving:

• Enterprise search connected to all company knowledge sources
• Making knowledge available and digestible via Gen AI
• Finding the optimal UX for the new age of AI-powered enterprise applications
• Building a semantic representation of the organization and all of the people and subject matter experts
• Improving Retrieval Augmented Generation (RAG) quality across varied data distributions/domains + handling conflicting and noisy data
• Crowdsourced data curation and learning from feedback that must work at smaller scales
• Access controls, scalability, high availability, data freshness, etc.
• [Future] Code Search, NL-to-SQL, Excel/Sheets

🧑‍💻 Tech Stack:

• Typescript/NextJS
• Python
• Postgres
• Hybrid Document Index (Vector DB / Keyword Index)
• AI/Deep-Learning (BERT style transformers, GPT, knowledge graphs, agents)
• Docker/Docker-Compose/Kubernetes