Capital One
Full Stack Engineer 5 - Global Workforce Services - AI Automation
$209K–$262K
Richmond, VA +1 · Full-time · Posted Oct 19, 2026
- Location
- Richmond, VA
McLean, VA - Experience
- At least 6 years in software engineering and at least 3 years with public cloud platforms, cloud-based productivity tools, or virtualization technologies. Additional preferred experience includes multiple thresholds from 1+ to 9+ years.
- Education
- Bachelor's Degree or higher in Computer Science or a related quantitative field; Master’s Degree in Computer Science or a related field preferred.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Leads engineering projects and teams building full-stack, cloud-based systems and integrating AI agents into enterprise facilities and physical-security applications.
What you'll do
- Architect responsive web interfaces and build resilient microservices and APIs that support real-time AI responses.
- Integrate rule-based, retrieval-augmented, and generative AI systems with enterprise systems, databases, third-party APIs, and legacy software.
- Provide technical leadership across teams, shape architecture and technology direction, and mentor engineers.
What they ask for
- Bachelor's Degree or higher in Computer Science or a related quantitative field.
- At least 6 years of experience in software engineering (Internship experience does not apply).
- At least 3 years of experience with public cloud platforms (AWS, GCP, Azure), cloud-based productivity tools, or virtualization technologies.
Nice to have
- Master’s Degree in Computer Science or a related field.
- The posting lists additional preferred experience in RAG pipelines, agentic AI, LLM frameworks, programming, cloud systems, and technical leadership.
Pay
$229,900 - $262,400 USD base salary (McLean, VA); $209,000 - $238,500 USD base salary (Richmond, VA)
Tools
Next.js, React, TypeScript, Tailwind CSS, Python/FastAPI, Node.js/TypeScript, AWS, GCP
AI focus
Build and integrate real-time AI chat and agent interfaces, AI agents, RAG pipelines, and unified rule-based, retrieval-augmented, and generative AI production systems.
Model-written summary · the original posting is authoritative