Capital One
Staff Full-Stack Engineer
$245K–$307K
Chicago, IL +1 · Staff · Full-time · Posted Oct 15, 2026
- Location
- Chicago, IL
McLean, VA - Experience
- At least 7 years across the specified basic-qualification areas. Preferred experience includes 10+ years in several areas, 8+ years in database systems and public cloud, 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; preferred Master's Degree in Computer Science or Software Engineering.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization.
About the job
Leads technical vision and hands-on engineering for banking platforms, modernizing monoliths into microservices and event-driven systems while guiding architecture, implementation, and engineering teams.
What you'll do
- Define technical direction, design and implementation quality, and platform strategy and API standards.
- Modernize monolithic systems into microservice architectures and event-driven platforms; lead cross-divisional technical initiatives.
- Mentor engineers and share technical expertise while contributing hands-on across multiple projects.
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 to solve systemic development challenges.
Pay
$244,700 - $279,200 USD base salary (Chicago, IL); $269,100 - $307,200 USD base salary (McLean, VA)
Tools
AWS, Microsoft Azure, Google Cloud, JavaScript, TypeScript, Go, Java, Python
AI focus
Preferred expertise applying agentic AI coding tools to systemic development challenges; preferred experience designing and building distributed HPC and ML systems.
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