Besimple AI is a YC-backed startup from X25 batch. We provide training and evaluation data to AI labs, starting with audio. Our mission is to bring AI into the real world safely. We believe that AI can meaningfully empower humanity only if we put safety first. We’re a small, nimble team of passionate builders who believe humans must remain in the loop. With Besimple AI, you get to work with all parts of AI data, from collection to curation, you will learn how to build highest quality dataset that can extend model capabilities for tomorrow.
We’re early but moving fast:
Stage: Seed funded
Users: AI labs building audio or multi-modal language models
If you like working close to users, shipping quickly, and owning big pieces of product, you’ll probably enjoy this.
About the role
As our Founding Engineer, you’ll be one of the very first people on the team and a core partner to the founders. You’ll:
Own large pieces of the product and stack end-to-end
Help choose our architecture, tools, and engineering practices
Ship quickly with real users, then iterate based on feedback
Shape the culture of the engineering org we’ll build around you
This is not a narrow “tickets” role — it’s closer to being a co-founder without all the fundraising/admin overhead.
What you’ll do
In your first 6–12 months, you might:
Design, build, and ship features across the stack — from data models and APIs to polished UI
Work directly with founders and customers to understand problems and turn fuzzy requirements into simple, shipped solutions
Set up the foundations of our infrastructure: CI/CD, observability, testing, security, and performance baselines
Make key technical decisions (languages, frameworks, architecture) and document the reasoning so others can build on it
Help interview, hire, and onboard future engineers and contractors
Roll up your sleeves on whatever is needed — product, support, docs, or debugging gnarly production issues
Building data pipelines, evaluation toolings and improving our annotation platform.
You might be a good fit if
You’ve shipped real products end-to-end at a startup or small, fast-moving team
You’re comfortable working across the stack, including mobile development
You like owning problems, not just tasks: you care about the user outcome, not just the code
You’re happy working with ambiguous specs and iterating directly with founders and users
You value clean, pragmatic engineering: tests, good abstractions, and simple designs over cleverness
You communicate clearly, give and receive feedback well, and enjoy collaborating closely with non-engineers
Nice to have (but not required)
Experience at an early-stage startup (seed/Series A or earlier)
Exposure to AI / data / infra / devtools / audio (depending on your domain)
Comfort with our current stack: [e.g. React, TypeScript, Node, Firebase/Firestore, GCP]
Experience setting up analytics, experimentation, or data pipelines
Prior work on developer tools, internal tools, or workflows where reliability really matters
Why you might be excited to join
High ownership: You’ll influence product scope, technical direction, and engineering culture from day one.
Massive impact: Your work will directly shape what Besimple becomes over the next few years.
Mentorship & visibility: Work directly with the founders on product, fundraising, and strategy — not just code.
Compensation: Competitive salary plus meaningful early equity
Flexibility: We are in-person in Redwoodt City, CA with flexible hybrid options
Benefits: Health, dental, vision, 401k, etc.
Why you might not be excited
You prefer clear, stable requirements over messy, fast iteration
You want a large team with established processes rather than helping create those processes
You’re looking for a narrow specialist role instead of doing a bit of everything
You’re not comfortable with the risk/ambiguity that comes with very early-stage startups
About Besimple AI
We are building the data layer for AI, starting with audio.
We start with data collection, curating our own proprietary set of diverse conversational data covering a wide range of languages, dialects and accents. We then leverage human expert audio annotators and our own annotation platform to process audio data for Automatic Speech Recognition.
With human level transcription and diarization, our data help push the audio model frontier. Today we have over millions of hours of conversational data, and growing.
If you need audio data for training or evaluating your voice models or voice agents, reach out! We offer flexible licensing deals that work for startups and enterprises, with minimal process.
