Distinguished Engineer (Decisioning Platform)

About the role

The Card Decisioning Platform team at Capital One is responsible for enabling the business to manage risk and drive value across the customer lifecycle by providing real-time, accurate, secure, and AI-powered decision-making solutions for customer transactions, fraud detection, alerts, credit inquiries, and applications across card, lending, and banking products.

Responsibilities

• Articulate and evangelize a bold technical vision for your area of responsibility
• Decompose complex problems into practical and operational solutions by willing to write code and create low-level designs
• Ensure the quality of technical design and implementation
• Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability, observability, 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
• Able to apply the right level of judgement on delegation of work to mentor individual contributors and thereby help to mentor and coach next generation of distinguished engineers

Qualifications

• Bachelor’s Degree
• At least 7 years of experience as hands-on full stack or backend technologist
• At least 5 years of professional experience coding in commonly used languages like Java, Python, Go
• At least 5 years of experience in software engineering, architecture, solution architecture, site reliability engineering
• At least 3 years of experience in cloud native technologies (AWS, Microsoft Azure, Google Cloud)

Preferred Qualifications

• Master's Degree in Computer Science or a related field
• At least 10 years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment, and production support
• At least 8 years of experience in designing large-scale and resilient applications
• At least 3 years of experience with solutioning a large-scale platform
• Familiarity with AI agents, agent orchestration, and architecture