Senior Staff Full-Stack Engineer — Global Payments (Remote)

Capital One; Des Moines (IA); Remote; USD 286,000 - 327,000; Full time

Job summary

Capital One is seeking a Senior Staff Full-stack Engineer (Remote-Eligible) to join the Global Payment Network. You will guide technical strategy, lead high-impact projects, and mentor engineers while delivering scalable, cloud-native solutions across payments platforms.

The role emphasizes AI-enabled tooling, performance, and enterprise-grade design across distributed systems. The position supports remote work and offers exposure to modern fintech, large-scale data processing, and

Qualifications

• Bachelor's degree or higher in Computer Science or a related quantitative field.
• At least 9 years of experience in software engineering, solution architecture, and cloud/data disciplines.
• Experience with cloud computing (AWS, Azure, Google Cloud) and data architectures.

Responsibilities

• Articulate and evangelize a bold technical vision for your domain.
• Decompose complex problems into practical operational solutions.
• Ensure quality of technical design and implementation.
• Lead modernization from monolithic to microservice architectures.

Skills

Web technologies

Distributed HPC & ML systems

Data architecture

Mentoring engineers

AI coding tools

Networking protocols

FinTech/payments domain

Education

Bachelor’s Degree or higher in CS or related field

Master’s Degree in CS or Software Engineering

Tools

AWS

Azure

Google Cloud

Go

Java

JavaScript/TypeScript

Python

Rust

C#

Scala

Job description

Capital One is seeking a Senior Staff Full-stack Engineer (Remote-Eligible) to join the Global Payment Network. You will guide technical strategy, lead high-impact projects, and mentor engineers while delivering scalable, cloud-native solutions across payments platforms.

The role emphasizes AI-enabled tooling, performance, and enterprise-grade design across distributed systems. The position supports remote work and offers exposure to modern fintech, large-scale data processing, and