Senior Lead Software Engineer, Full Stack (Enterprise Platforms Technology)

Overview

At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors, who solve real problems and meet real customer needs. We are seeking Full Stack Software Engineers who are passionate about marrying data with emerging technologies.

What You’ll Do

• Design and build API layers that enforce access control semantics, ensuring consumers only receive data they're authorized to access
• Lead architecture proofs-of-concepts that resolve open technical questions — then drive findings into production-ready decisions
• Own technical workstreams end-to-end: scope definition, interface contracts, implementation, and operational readiness
• Operate in an AI-augmented engineering model: design the tools, quality gates, and validation patterns that accelerate delivery
• Design graph data models that represent complex entity relationships at enterprise scale
• Collaborate across organizational boundaries with architecture, product, and data engineering counterparts
• Drive infrastructure and topology decisions backed by performance data, not assumptions
• Define and validate non-functional requirements (latency, throughput, availability) rooted in documented business needs

Basic Qualifications

• Bachelor’s Degree
• At least 6 years of experience in software engineering (Internship experience does not apply)
• At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud)

Preferred Qualifications

• Master’s Degree
• 9+ years of experience in at least one of the following: Go, Java, or Python
• 4+ years of experience with AWS services (Neptune, DynamoDB, Lambda, Step Functions, ECS, IAM)
• 5+ years of experience with designing and operating graph databases or large-scale relationship-oriented data systems
• 9+ years of experience with system design at scale, including distributed caching, event-driven architectures, and dual-write or migration patterns
• 2+ years of experience with access control models and data governance at the platform layer
• Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion