Capital One
Sr. Staff Cloud Engineer (Cloud Asset Intelligence)
$286K–$392K
McLean, VA +5 · Senior Staff · Full-time · Posted Oct 7, 2026
- Location
- McLean, VA
San Francisco, CA
Richmond, VA
Chicago, IL
New York, NY
Plano, TX - Experience
- At least 9 years in software engineering and at least 6 years in cloud engineering; preferred experience includes 12+ years coding, 8+ years with public cloud platforms, 5+ years architecting multi-tenant platforms, and 4+ years using knowledge graphs.
- 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 for this position.
About the job
Leads cloud asset inventory and intelligence initiatives, shaping secure AI-native platforms and modernizing cloud systems across the enterprise.
What you'll do
- Set technical vision and lead architecture, design, and implementation for cloud asset intelligence platforms.
- Modernize monolithic systems into microservices and event-driven platforms; guide platform strategy and API standards.
- Lead responsible adoption of AI and automation, cross-team projects, and mentoring of engineers.
What they ask for
- Bachelor's degree or higher in Computer Science or a related quantitative field.
- At least 9 years of software engineering experience.
- At least 6 years of cloud engineering experience.
Nice to have
- 12+ years coding with Java, Scala, Python, Go, or Node.js; 8+ years with public cloud platforms (AWS, GCP, Azure, OCI).
- Experience with multi-tenant platform architecture, knowledge graphs, asset management, and AI-native platforms.
Pay
$286,200 - $326,700 USD base salary (Chicago, IL); $314,800 - $359,300 USD base salary (McLean, VA); $343,400 - $392,000 USD base salary (New York, NY); $286,200 - $326,700 USD base salary (Plano, TX); $286,200 - $326,700 USD base salary (Richmond, VA); $343,400 - $392,000 USD base salary (San Francisco, CA)
Tools
Java, Scala, Python, Go, Node.js, AWS, GCP, Azure
AI focus
Lead adoption and responsible use of AI and automation to improve cloud platform and engineering workflow scalability, reliability, and efficiency; build AI-native platforms or integrate AI into operational tools for automated intelligence and actionable insights.
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