Drimva

Capital One

Mobile Engineer 4 (Android)

$197K–$225K

McLean, VA · Full-time · Posted Oct 14, 2026

Experience
At least 4 years of professional software engineering experience and at least 3 years building native mobile applications; preferred: 4+ years building native mobile applications.
Education
Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
Visa sponsorship
Will not sponsor a new applicant for employment authorization or provide immigration-related support for this position.

About the job

Leads hands-on Android mobile engineering, architecture, and delivery of scalable customer-facing features, while mentoring engineers and promoting AI-native development practices.

What you'll do

  • Partner with product, design, and engineering teams to build high-quality mobile features and lead mobile architecture, API design, and reusable components.
  • Lead client BFF and SDUI design and development, and establish feature-flag and staged-rollout practices.
  • Mentor engineers and champion quality, performance, accessibility, and agentic AI adoption.

What they ask for

  • Bachelor's Degree or higher in Computer Science or a related quantitative field.
  • At least 4 years of professional software engineering experience; internship experience does not apply.
  • At least 3 years building native mobile applications for Android (Kotlin) or iOS (Swift).

Nice to have

  • Experience with native UI frameworks, mobile automated testing, performance optimization, and scalable or modular architectures.
  • Experience with BFFs, GraphQL, gRPC/Protobuf, SDUI, staged rollouts, agentic AI coding tools, or on-device ML frameworks.

Pay

USD $197,300 - $225,100 base salary (McLean, VA)

Tools

Kotlin, Swift, SwiftUI, Jetpack Compose, Swift Testing, XCUI, JUnit, Espresso

AI focus

Champion adoption of agentic AI tools and mentor engineers in AI-native development practices; expertise with agentic AI coding tools and AI-assisted workflows is preferred.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)