Distinguished Engineer

Capital One Capital One · Banking · McLean, VA +2

Distinguished Engineer role focused on defining and delivering the next evolution of engineering within People Tech, shifting from domain-centric to a system-driven model. The role involves advancing Engineering and Operational Excellence, reducing duplication, and enabling faster, more reliable delivery through standardized execution and reuse. Responsibilities include articulating technical vision, decomposing complex problems, ensuring quality, serving as an expert on non-functional characteristics, mentoring, and architecting high-scale, reusable capabilities. Requires experience in designing and building distributed AI/ML systems and cloud computing.

What you'd actually do

  1. Articulate and evangelize a bold technical vision for your domain
  2. Decompose complex problems into practical and operational solutions
  3. Ensure the quality of technical design and implementation
  4. Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability
  5. Continue learning and injecting advanced technical knowledge into our community

Skills

Required

  • Software engineering
  • solution architecture
  • Enterprise architecture and design patterns
  • designing and building distributed AI and ML systems
  • Cloud computing (AWS, Microsoft Azure, Google Cloud)

Nice to have

  • Computer Science or a related field
  • software engineering
  • platform engineering
  • architecture
  • Java
  • Python
  • Go
  • JavaScript/TypeScript
  • Swift
  • system development lifecycle
  • public or private cloud technologies
  • interactive AI tooling
  • cross-domain solutions

What the JD emphasized

  • designing and building distributed AI and ML systems
  • Cloud computing (AWS, Microsoft Azure, Google Cloud)
  • system-driven model
  • autonomous operations
  • build once, scale everywhere architecture

Other signals

  • designing and building distributed AI and ML systems
  • Cloud computing (AWS, Microsoft Azure, Google Cloud)
  • system-driven model where capabilities are defined once and executed consistently through shared platforms
  • autonomous operations
  • build once, scale everywhere architecture