Brainbaselabs

Brainbaselabs

Founding Engineer

San Francisco

Sponsorship not specifiedDetected 272 days ago
TypeScriptPythonReactNext.jsAWSCI/CDWebSocketsMachine LearningLLMsHubSpotVoIPResearchCommunication

About the role

  • As part of our founding team, you will have a high agency role in bringing AI to the enterprise: shipping new features, talking to users and shaping company culture for other team members to come.
  • You will work one-on-one with our CEO and founding team to primarily iterate based on customer feedback, help with infrastructure scaling (cloud and on-premise) and improve our underlying proprietary agent system.
  • We think you should apply if the following sounds like you:

Responsibilities

  • 🧠 Why should I join Brainbase and not start my own startup?
  • But startups are (famously) hard, and it's usually good practice to see how a good one is run before you start your own.

Requirements

  • Resilient - You don't quit when something is difficult, only when you have realized a better way to do it
  • Decisive - You can make informed decisions under stress with incomplete data, and move on to the next task (no hedging)
  • Fun - You can smile/joke/enjoy yourself through the pain and the slog, and can lift up others even when things are objectively not going well
  • 2+ years of software engineering experience (new grads encouraged since pet projects count)
  • Some experience with LLMs (OpenAI API, Langchain, HuggingFace, etc.)
  • Proficiency in AWS, cloud deployment, CI/CD
  • Experience with ORMs (Prisma, Drizzle, etc)

Skills

  • Brainbase is to AI Employees what Retool is to internal tools.
  • Brainbase enables businesses to create those AI Employees.
  • WHO'S A GOOD FIT?

Company info

  • If you're accepted into our team, there is no question that we believe you're capable of running your company.

Visa & Work Authorization

  • US work permit (we do not currently sponsor H1-Bs, OPTs are fine)

This listing is sourced directly from Brainbaselabs's careers page and normalized into a canonical job model.