Capital One
Full-stack Engineer 5 (Senior Manager, IC)
$209K–$262K
McLean, VA +1 · Manager · Full-time · Posted Oct 26, 2026
- Location
- McLean, VA
Richmond, VA - Experience
- At least 6 years in software engineering and at least 3 years in public cloud platforms, cloud-based productivity tools, or virtualization technologies. Preferred experience includes 9+ years coding with more than two listed languages, plus additional experience requirements ranging from 1 to 5+ years.
- Education
- Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Leads engineering teams and delivers AI-powered, cloud-based risk management systems that meet regulatory needs and serve customers.
What you'll do
- Lead a portfolio of technology projects and developers building distributed microservices and full-stack solutions for regulatory needs.
- Provide technical leadership across teams, shaping system architecture, platform roadmaps, and long-term technology direction.
- Design and implement reliable, high-performance distributed or cloud-native systems in collaboration with product managers, architects, and engineering partners.
What they ask for
- Bachelor's Degree or higher in Computer Science or a related quantitative field.
- At least 6 years of software engineering experience (internship experience does not apply).
- At least 3 years of experience with public cloud platforms, cloud-based productivity tools, or virtualization technologies.
Nice to have
- Master’s Degree in Computer Science or a related field.
- Experience with modern AI-based coding tools and interactive AI tooling beyond basic code completion.
Pay
$229,900 - $262,400 USD base salary (McLean, VA); $209,000 - $238,500 USD base salary (Richmond, VA)
Tools
Java, Scala, Python, Go, Node.js, JavaScript, TypeScript, Docker
AI focus
Build proprietary risk management solutions powered by state-of-the-art AI; the team also uses machine learning for risk prevention and issue detection.
Model-written summary · the original posting is authoritative