Capital One
Full-stack Engineer 5 (Senior Manager, IC)-Risk Tech
$209K–$286K
New York, NY · Manager · Full-time · Posted Sep 24, 2026
- Experience
- At least 6 years in software engineering and at least 3 years with public cloud platforms, cloud-based productivity tools, or virtualization technologies. Preferred experience includes 9+ years coding in more than two listed languages; other preferred experience requirements range from 1+ to 5+ years.
- 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 engineering teams and delivers AI-powered, cloud-native risk management solutions that meet regulatory needs.
What you'll do
- Lead technology projects and developers building distributed microservices and full-stack solutions for regulatory needs.
- Guide architecture, technical direction, platform roadmaps, and shared services across teams.
- Design and implement reliable, high-performance distributed or cloud-native systems in collaboration with product and architecture partners.
What they ask for
- Bachelor's Degree or higher in Computer Science or a related quantitative field.
- At least 6 years of experience in software engineering; 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 IDE copilots, interactive AI tooling, and technology strategy.
Pay
$229,900 - $262,400 USD base salary; $250,800 - $286,200 USD base salary; $209,000 - $238,500 USD base salary
Tools
Java, Scala, Python, Go, Node.js, JavaScript, TypeScript, AWS
AI focus
Build and deploy proprietary risk management solutions powered by state-of-the-art AI; use machine learning to help prevent risks and automatically detect issues. AI tooling is also a preferred way to accelerate engineering productivity.
Model-written summary · the original posting is authoritative