Senior Lead Software Engineer, Full Stack (golang, Python, Genai) (cloud Operations Resilience Engineering)

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

Senior Lead Software Engineer role focused on Cloud Operations Resilience Engineering, driving enterprise vision for AI-driven systems to automate governance, risk management, and compliance. The role involves designing and implementing intelligent guardrails, leveraging ML for insights, and pioneering modern cloud-native designs. Requires hands-on coding, architecture reviews, and collaboration with data scientists and risk partners. Experience with Golang, Python, and AWS is preferred.

What you'd actually do

  1. Shape and advance the technical vision and long-term roadmap for Enterprise Architecture tooling, transforming how application health, compliance, and governance are managed at scale.
  2. Design and champion enterprise-wide architectural patterns, utilizing automated, AI-driven solutions to enforce real-time governance, risk management, and regulatory compliance across all Capital One applications.
  3. Infuse industry trends into our ecosystem—such as event-driven architectures, mesh data topologies, and next-gen cloud-native design—ensuring systems are resilient, highly secure, and horizontally scalable.
  4. Oversee and de-risk the architectural design, testing, deployment, and optimization of highly critical distributed systems, microservices, and full-stack platforms.
  5. Maintain deep technical expertise and actively write code, conduct architecture reviews, create proofs-of-concept (PoCs), and rigorously evaluate codebases to validate technical directions.

Skills

Required

  • Golang
  • Python
  • AWS
  • Kubernetes
  • Docker
  • distributed systems
  • microservices
  • full-stack platforms

Nice to have

  • Java
  • TypeScript
  • NoSQL databases
  • event-driven architectures
  • mesh data topologies
  • cloud-native design
  • Master's Degree
  • open source frameworks
  • interactive AI tooling

What the JD emphasized

  • AI-driven systems
  • intelligent guardrails
  • governance
  • compliance
  • risk management
  • automated, AI-driven solutions
  • LLMs
  • automated compliance agents

Other signals

  • AI-driven systems to automate and scale governance and oversight
  • intelligent guardrails that ensure architectural excellence and compliance
  • leveraging machine learning to deliver real-time insights and proactive risk management
  • automated, AI-driven solutions to enforce real-time governance, risk management, and regulatory compliance
  • experiment with emerging technologies (such as LLMs and automated compliance agents)