Capital One Lead Software Engineer Data & AI – Capital One 

United States, Virginia, Richmond 

316099277

What You’ll Do

• Lead a portfolio of diverse technology projects and a team of developers with deep experience in large-scale distributed systems, data security and governance, and cloud-native architecture. Make impactful, hands-on contributions throughout the project lifecycle, from scoping, design to coding and operations.

• Share your passion for staying on top of tech trends, experimenting with and learning new technologies on Security Data Management Platform, Agentic AI, Cloud Data Warehouse, etc, participating in internal & external technology communities, mentoring other members of the engineering community.

• Collaborate with product managers, translate product requirements into engineering tasks, make trade-off calls to balance delivery timelines and engineering best practices.

• Own and drive cross functional partnerships with teams spanning Engineering, Platform, Design, Data Science, Security and GTM teams, and partner closely with theleadership/stakeholdersof various teams within these teams.

• Drive innovations on building AI-enabled agents, fine-tune LLM models for data classification and sensitive data detection.

Basic Qualifications

• Bachelor’s Degree

• At least 4 years of experience in software engineering (Internship experience does not apply)

• At least 2 year experience with cloud computing(AWS, Microsoft Azure, or Google Cloud).

• At least 3 years experience in programming language; Java, Python, C++, Rust or Go.
  

Preferred Qualifications

• Master’s Degree

• Prior experience in building

  Data Security Posture Management
  (DSPM) system is a huge plus.

• Proficient in SQL. Hands-on experience with RDBMS and NoSQL databases.

• Hands-on experience with Container Orchestration services including Docker and Kubernetes.

• Experience in cloud-based lakehouses such as Databricks, Snowflake, AWS Athena, etc.

• Experience in open source data governance/catalog platforms such as Datahub, OpenMetadata or Atlas is a plus.

• Hands-on experience in building production scale agentic AI systems. Familiar with tools such as Langchain, Langgraph, and MCP.

• Hands-on experience in fine-tuning LLM, and deployed to productions to serve customers.

• 2+ years of experience in Agile practices