Customer Engineer at Danswer (W24)
$120K - $240K  ‱  0.30% - 1.50%
Open Source AI Assistant and Enterprise Search
San Francisco, CA, US
Full-time
1+ years
About Danswer

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 đŸ€Ż

About the role
Skills: Kubernetes, Google Cloud, Docker, Microsoft Azure, Amazon Web Services (AWS)

💡 About the role

As our first Customer Engineer, you should expect to:

  • Act as the primary technical advisor to Danswer’s rapidly growing customer base, providing expert support and building strong relationships
  • Guide customers through their self-hosted deployments across different clouds (AWS, GCP, Azure, etc.) and deployment methods (Docker Compose, Kubernetes, AWS ECS, Helm, etc.)
  • Debug and patch tricky, deployment-specific issues with customers  
  • Contribute features to systematically eliminate common issue points during deployment
  • Create a seamless onboarding experience by developing comprehensive documentation that enables open-source users to easily deploy Danswer in their own cloud environments 
  • Work with customers to find the best use cases for Danswer, maximizing our impact and value
  • Be the voice of the customer and bridge the gap between customers and product. Relay product insights and customer feedback to founders/engineering and help shape the direction of product

🚀 You’ll be successful in this role if you


  • Have 2+ years of experience as a Customer Engineer / Solutions Engineer / Deployed Engineer at a enterprise facing software company OR have 2+ years of experience in DevOps / Software Engineering and have an interest in shifting to a more customer-facing role
  • Experience with Docker/Kubernetes, cloud technologies (AWS, GCP, Azure), and on-prem/cloud deployments
  • Are a great multitasker, able to stay organized among competing priorities, and can pivot and adapt at a moment’s notice
  • Excellent communication skills, with a strong ability to collaborate with others (both teammates and external customers). Ability to explain complex engineering/infrastructure concepts and tradeoffs to customers in a simple way.
  • Experience working in a fast-moving startup and in small teams with minimal guidance.

⭐ Bonus points

  • You’ve worked closely with customers to help them self-host software on their own infrastructure
  • Experience with technical writing / large scale documentation
  • Experience with Typescript/React/NextJS, Python, Relational DB (Postgres), and Vespa or Elasticsearch
  • Experience (or even just interest) in information retrieval and AI (NLP, Deep Learning, GenAI)
Technology

đŸ’Ș 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

đŸ§‘â€đŸ’» 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
Interview Process
  • Non-technical Phone Screen
  • Cloud Infrastructure Interview (45 mins)
  • 3 Day Onsite Trial (fully covered + compensated)

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