Distinguished Engineer, Full Stack

Role Overview

• Articulate and evangelize a bold technical vision for your domain
• 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
• Lead proof-of-concept development for emerging AI frameworks and architectural patterns
• Collaborate with other Finance Technology towers reviewing architectures and designs outside your immediate domain and contributing a cross-cutting perspective that raises the bar org-wide
• Champion AIOps practices — driving platform reliability through AI-assisted anomaly detection, automated remediation, and predictive alerting across the portfolio

Requirements

• Bachelor’s Degree
• At least 7 years of experience in the following: Software engineering and solution architecture, Enterprise architecture and design patterns, Designing and building distributed HPC and ML systems, Full ML development lifecycle using AI and ML frameworks, Cloud computing (AWS, Microsoft Azure, Google Cloud), Data engineering
• Preferred Qualifications: Bachelor's or Master's in Computer Science, Applied Mathematics, or a related technical field, 10+ years of experience in one or more of: software engineering and solution architecture, enterprise architecture and design patterns, distributed HPC and ML systems, ML development lifecycle, cloud computing, or data architecture, 10+ years of hands-on coding in commonly used languages Python, Java, Go, Scala, JavaScript/TypeScript, or similar; you are a working engineer, not a former engineer, 8+ years owning the full SDLC, conception through architecture, implementation, testing, deployment, and production support; you have been paged and you have fixed it, Demonstrated AI-native engineering practice across all three layers: Daily use of AI coding assistants to accelerate productivity, utilizing capabilities well beyond basic code completion, Spec/intent driven development, AI embedded in CI/CD and SDLC tooling — test generation, spec validation, code review augmentation, Production experience building LLM-backed or agentic systems — prompt engineering, evaluation frameworks, observability, and guardrails included, Experience working directly with quantitative analysts or data scientists — model development lifecycles, feature pipelines, backtesting, ML deployment, and the rigor to validate what a model is actually doing.

Tech Stack

• AWS
• Azure
• Cloud
• Java
• JavaScript
• Python
• Scala
• SDLC
• TypeScript
• Go

Benefits

• Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.