Distinguished Engineer (Remote - Eligible)

Capital One is a financial services company that is redefining banking in the cloud. The Distinguished Engineer will drive innovation, optimize business outcomes, and lead technical contributions while mentoring talent and creating intelligent risk management products using advanced technologies.

Responsibilities:

• Articulate and evangelize a bold technical vision for embedding AI and automated code transformation into the developer lifecycle
• Decompose complex problems into practical and operational solutions
• Ensure the quality of technical design and implementation
• Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability
• Continue learning and injecting advanced technical knowledge into our community
• Handle several projects simultaneously, balancing your time to maximize impact
• Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community
• Ensure Code is of the highest quality & standard while being an active contributor and reviewer on critical repos of the application
• Develop full stack applications with a product engineering mindset, spanning frontend and backend ecosystems that balance simplicity with flexibility

Requirements:

• Bachelor's Degree
• At least 7 years of experience in Software engineering and solution architecture
• At least 7 years of experience in Enterprise architecture and design patterns
• At least 5 years of experience in Cloud computing (AWS, Microsoft Azure, Google Cloud)
• At least 5 years of experience in Data architecture including Event Driven and Real-Time architectures
• Bachelors' or Master's Degree in Computer Science or a related field
• 10+ years of experience in Software Engineering and solution architecture
• 10+ years of professional experience coding in commonly used languages like Java, Python, Go, JavaScript/TypeScript, Swift, etc
• 8+ years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment and production support
• Experience in applying Artificial Intelligence or Machine Learning concepts to engineering challenges (e.g., anomaly detection, test optimization, intelligent testing)
• Deep practical knowledge of Site Reliability Engineering (SRE) principles, chaos engineering, and advanced Observability tooling (e.g., OpenTelemetry, Prometheus, Tracing)
• Experience in implementing Artificial Intelligence or Artificial Intelligence-enabled solutions