Capital One
Staff Full-stack Engineer (Remote-Eligible) - Global Payment Network
$245K–$307K
McLean, VA +4 · Staff · Full-time · Posted Oct 1, 2026
- Location
- McLean, VA
US Remote
Richmond, VA
Plano, TX
Riverwoods, IL - Experience
- At least 7 years in each of the listed basic-qualification areas. Preferred experience includes 10+ years in several areas, 8+ years in others, 5+ years mentoring senior engineers, and 2+ years leading cross-domain architectural reviews.
- Education
- Bachelor's Degree or higher in Computer Science or a related quantitative field
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Leads hands-on architecture and development of scalable payment-network systems, modernizing platforms while setting technical direction and mentoring engineers.
What you'll do
- Define technical vision, design and implementation quality, and standards for payment-network platforms.
- Modernize monoliths into microservices and event-driven systems; shape platform strategy and API standards.
- Lead cross-team technical work and mentor engineers while contributing hands-on.
What they ask for
- Bachelor's Degree or higher in Computer Science or a related quantitative field.
- At least 7 years of experience in software engineering and solution architecture, enterprise architecture and design patterns, cloud computing, and data architecture.
Nice to have
- Master’s Degree in Computer Science or Software Engineering.
- Experience with agentic AI coding tools, AI-driven development, payment/fintech systems, and distributed real-time data platforms.
Pay
Remote (Regardless of Location): $244,700 - $279,200 USD base salary; McLean, VA: $269,100 - $307,200 USD base salary; Plano, TX: $244,700 - $279,200 USD base salary; Richmond, VA: $244,700 - $279,200 USD base salary; Riverwoods, IL: $244,700 - $279,200 USD base salary
Tools
AWS, Microsoft Azure, Google Cloud, JavaScript, TypeScript, Go, Java, Python
AI focus
Apply automation and AI-native engineering to gain real-time insights and improve transaction processing, fraud and risk mitigation; use agentic AI coding tools and AI-driven development practices.
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