Full Stack Engineer

Ai, Inc
New York, NY, United States
6 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$200,000.0 - $350,000.0
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Data Analysis Databases Distributed Systems Python (Programming Language) Node.Js Software Engineering Systems Architecture TypeScript Real Time Systems ReactJS
+8 more
Large Language Models Backend Agentic-AI Event Driven Architecture Low Latency Real Time Data Front End Software Development Golang

Job description

  • AI-native financial products: Build intelligent applications that automate complex financial workflows, analyze data, and turn decisions into actions.
  • Complex backend systems: Architect APIs, distributed services, transaction processing systems, and scalable infrastructure.
  • Exceptional frontend experiences: Build fast, intuitive, highly interactive products that make complicated financial data and workflows simple.
  • Real-time systems: Engineer products where performance, reliability, data accuracy, and low latency actually matter.
  • 0*1 products: Take ambitious ideas from technical design to production, owning architecture, implementation, and user experience.

Requirements

A true 50/50 full-stack engineer. Not a frontend engineer who occasionally writes APIs. Not a backend engineer who can tweak a React component. Someone genuinely exceptional on both sides.

  • 5+ years of professional software engineering experience
  • Strong frontend engineering experience with React, TypeScript, and modern frontend architecture
  • Deep backend experience with Python, Node.js, Go, or similar languages
  • Experience designing and scaling APIs, distributed systems, and production services
  • Strong understanding of databases, data modeling, and system architecture
  • Proven experience building complex products end-to-end
  • Experience owning meaningful 0*1 engineering initiatives
  • Strong product instincts and the ability to make thoughtful technical tradeoffs
  • Comfortable working in fast-moving, high-ownership engineering environments

Bonus points for:

  • Fintech, payments, trading, banking infrastructure, or financial data platforms
  • AI agents, LLM-powered applications, or intelligent automation
  • Real-time data systems, event-driven architectures, or high-throughput infrastructure
  • Founding engineering or early-stage startup experience

You don’t need to be an ML researcher or a financial expert. You need to be an exceptional engineer who can turn technically complex problems into extraordinary products.

Benefits & conditions

$200K-$350K Base + Equity NYC or San Francisco 5 Days In-Office, Hybrid flexibility

What happens when AI stops being a feature and starts becoming the infrastructure behind how money moves?

I’m looking for passionate full-stack engineers who want to build the next generation of AI-native fintech.

Think intelligent financial systems, real-time decision-making, complex transaction infrastructure, and products that automate workflows previously requiring entire teams.

Not another fintech dashboard. Not another AI wrapper. We’re talking about rethinking how financial technology is built from the ground up.

The engineering challenges sit at the intersection of AI, distributed systems, financial infrastructure, and sophisticated product engineering.

We’re looking for engineers who can own the entire stack, from the architecture powering complex financial workflows to the interfaces that make incredibly sophisticated technology feel effortless.

About the company

Financial services is one of the largest, most technically complex industries in the world and much of its infrastructure still relies on fragmented systems, manual processes, and outdated workflows.

AI is creating an opportunity to rebuild that infrastructure. The engineers who thrive in this environment aren’t just writing code. They’re designing systems, making architectural decisions, shaping product direction, and solving problems that don’t have established playbooks.

Small team. Massive technical ownership. Hard engineering problems. xrbllit Products with real-world impact.

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