Intern - Tech (Visiting)
About this role
What You'll Do
- Ship fast, learn faster: We deploy daily, not monthly
- Talk to users, shape the roadmap: Sit in with founders on calls that shape what we build
- Train AI agents: Help build LLM-powered testers that explore, learn, and adapt in real time
- Work across the stack: Python, TypeScript, cloud infra, from commit to production
- Turn prototypes into production: Run real experiments on models, embeddings, and retrieval pipelines
What We're Looking For
- Relentless drive: You execute fast, adapt faster
- Hackathon scar tissue: You've shipped projects with no safety net
- Fluency with AI/LLMs: LangChain, vector stores, prompt engineering
- Full-stack firepower: Frontend, backend, infra, no silos
- Product obsession: You care more about outcomes than outputs
- Experimental instinct: You build → test → learn → repeat
Ideal Background
There's no perfect pedigree. We hire for mindset, not credentials. That said, you might have:
- Shipped AI features in a side project
- Built something from 0 to 1
- Thrived in chaos with high ownership
Why Now
AI is rewriting software development.
But shipping still breaks on testing.
Engineering leaders are desperate to release faster without lowering quality. They can’t do it with manual QA or brittle test automation. They will need autonomous agents , full stop.
Five years from now, every high-velocity team will depend on AI-native QA. We’re building the platform that gets them there and would love for you to join us.
Company at a glance
As AI commoditises code generation, the bottleneck moves from writing software to trusting it. Verification is the layer that determines whether AI-generated code ships to production or stalls in review.
Code-level tests rot every time the implementation changes.
Product-level verification does not care how the code was written, only whether the product still does what users came to do.
Duku continuously simulates your users so you can trust every release, before it ships.
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