Capital One
Staff Full-stack Engineer
$245K–$307K
Riverwoods, IL +4 · Staff · Full-time · Posted Sep 21, 2026
- Location
- Riverwoods, IL
McLean, VA
Richmond, VA
Chicago, IL
Plano, TX - Experience
- At least 7 years in each of the listed basic-qualification areas. Preferred experience ranges from 2+ to 10+ years, depending on the area.
- Education
- Bachelor's Degree or higher in Computer Science or a related quantitative field; Master’s Degree in Computer Science or Software Engineering preferred.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Provides architectural leadership and hands-on engineering for rebuilding Capital One’s Settlement platform in the cloud, modernizing systems and guiding technical strategy.
What you'll do
- Define technical vision and guide architecture, design quality, and implementation for cloud platform modernization.
- Help migrate monolithic systems to microservices and event-driven platforms; contribute hands-on proof-of-concept work.
- Mentor engineers and influence platform strategy, API standards, and engineering practices across teams.
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.
- Expertise in the strategic application of agentic AI coding tools and experience in Spec-Driven Development.
Pay
$244,700 - $279,200 USD base salary (Chicago, IL); $269,100 - $307,200 USD base salary (McLean, VA); $244,700 - $279,200 USD base salary (Plano, TX); $244,700 - $279,200 USD base salary (Richmond, VA); $244,700 - $279,200 USD base salary (Riverwoods, IL)
Tools
AWS, Microsoft Azure, Google Cloud, JavaScript, TypeScript, Go, Java, Python
AI focus
Preferred expertise in applying agentic AI coding tools to systemic development challenges; preferred experience designing and building distributed HPC and ML systems.
Model-written summary · the original posting is authoritative