Distinguished Engineer - Risk Tech (Remote - Eligible)

About the position As a Distinguished Engineer at Capital One, you will be a part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Distinguished Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while driving towards strong technology solutions. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence, and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring internal talent and actively recruiting to keep building our community. Distinguished Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other material to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization. This role is part of the Risk Technology organization. In Risk Technology, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our business, our customers, or our communities. If you are ready to provide thought leadership and build engineering excellence across Capital One's engineering teams, come join us in our mission to change banking for good. Capital One is open to hiring a Remote Employee for this opportunity.

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

Nice-to-haves

• 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