Required Senior Backend Engineer
Description
This is not your typical engineering role.
If you're looking to pick up tickets, follow specs, and write clean services- this isnt for you.
But if you care about building systems that think, if you use AI to move faster than everyone else, and if you want real ownership over complex, high-scale problems – keep reading.
What we're actually building:
Were building systems that dont just process data, they make decisions.
Real-time, high-stakes, at scale.
Fraud isnt static. It evolves all the time so our systems need to evolve faster.
That means combining backend architecture, data, and AI into something smarter than traditional SaaS.
What youll actually do:
Design and build the core systems behind real-time fraud detection
Work on everything from ingestion pipelines to decision engines
Own what you build – from idea to production to iteration
Deal with scale, edge cases, failures, and ambiguity (a lot of it)
Use AI as part of your daily workflow – not as a gimmick, but as leverage
Help figure out better ways to build software in this new era.
What youll get here:
Real ownership (not ownership in slides)
Hard problems with real impact
A team that moves fast and expects you to keep up
Freedom to rethink how things should be built – not just maintain what exists
A chance to become a significantly stronger engineer by working differently
Stack (for context, not as a checklist):
Node.js / TypeScript
Distributed, event-driven architecture
Kafka
AWS
MongoDB + Postgres
Containers (Docker, Kubernetes / ECS).
Description
This is not your typical engineering role.
If you're looking to pick up tickets, follow specs, and write clean services- this isnt for you.
But if you care about building systems that think, if you use AI to move faster than everyone else, and if you want real ownership over complex, high-scale problems – keep reading.
What we're actually building:
Were building systems that dont just process data, they make decisions.
Real-time, high-stakes, at scale.
Fraud isnt static. It evolves all the time so our systems need to evolve faster.
That means combining backend architecture, data, and AI into something smarter than traditional SaaS.
What youll actually do:
Design and build the core systems behind real-time fraud detection
Work on everything from ingestion pipelines to decision engines
Own what you build – from idea to production to iteration
Deal with scale, edge cases, failures, and ambiguity (a lot of it)
Use AI as part of your daily workflow – not as a gimmick, but as leverage
Help figure out better ways to build software in this new era.
What youll get here:
Real ownership (not ownership in slides)
Hard problems with real impact
A team that moves fast and expects you to keep up
Freedom to rethink how things should be built – not just maintain what exists
A chance to become a significantly stronger engineer by working differently
Stack (for context, not as a checklist):
Node.js / TypeScript
Distributed, event-driven architecture
Kafka
AWS
MongoDB + Postgres
Containers (Docker, Kubernetes / ECS).
Requirements:
What we care about (beyond buzzwords):
Youve built real systems, not toy projects or just CRUD.
You understand distributed systems because youve dealt with their pain.
You can go deep when needed on performance, architecture, and trade-offs.
You dont wait for perfect specs, you figure things out.
You care about how things work, not just that they work.
AI is not optional here
You already use tools like Codex, Claude Code, Cursor – daily
You dont just autocomplete code – you think with AI
Youve built small tools / automations / experiments with LLMs
You know AI makes mistakes, and you know how to catch them
Youre curious about how engineering is changing, and you want to be ahead of it.
What we care about (beyond buzzwords):
Youve built real systems, not toy projects or just CRUD.
You understand distributed systems because youve dealt with their pain.
You can go deep when needed on performance, architecture, and trade-offs.
You dont wait for perfect specs, you figure things out.
You care about how things work, not just that they work.
AI is not optional here
You already use tools like Codex, Claude Code, Cursor – daily
You dont just autocomplete code – you think with AI
Youve built small tools / automations / experiments with LLMs
You know AI makes mistakes, and you know how to catch them
Youre curious about how engineering is changing, and you want to be ahead of it.
This position is open to all candidates.
