Capital One currently has 293 active AI-related job listings. The majority of these roles are focused on serving infrastructure, accounting for 28% of the total, followed closely by agents at 26% and post-training at 23%. Engineering is the dominant function, with 234 roles, and hiring is primarily concentrated in the United States. Frequent tech tags include model_serving, vector_db, and llm_observability, suggesting a focus on the operational aspects of AI deployment. In the last 30 days, Capital One posted 124 new AI roles, representing a 22% increase compared to the previous 30-day period.
Currently tracking 241 active AI roles, down 26% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $123k–$392k (avg $231k).
Capital One currently has 305 active AI-related roles in our index. The most common open titles are: Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) (9), Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) (8), Applied Researcher I (6), Distinguished Engineer (6), Applied Researcher II (5). Most positions are in Engineering and Research.
Capital One's active AI hiring is concentrated in: serving infrastructure (28%), agents (27%), post-training (23%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Capital One is hiring AI talent in: United States (299 roles), United Kingdom (3 roles), Canada (2 roles), Philippines (1 role).
Job postings at Capital One most frequently reference: model serving, vector db, fine tuning, llm observability, inference infra.
In the past 30 days, Capital One has posted 96 new AI-related roles. That is a -26% change versus the prior 30 days (130 → 96).
| Title | Stage | AI score |
|---|---|---|
| Manager, Data Scientist - Deposit Forecasting and Pricing Manager, Data Scientist role focused on developing behavior models for balance sheet portfolios using econometric time-series models and quantitative methods. The role involves applying machine learning, working with relational databases, and communicating models to stakeholders, including regulators. Requires experience in data analytics, machine learning, and relational databases, with a preference for advanced degrees and Python/Scala/R experience. | Data | 5 |
| Principal Associate, Quantitative Analysis This role involves partnering with business lines to enhance modeling and analytical frameworks, creating novel analytical solutions, and identifying opportunities to apply quantitative methods and automation to improve business performance. The role requires applying expertise in econometric, statistical, and machine learning methods to generate insights and provide technical guidance, with a focus on building cloud-based solutions grounded in data. |
| Data |
| 5 |
| Principal Data Analyst, Card Tech Workforce Strategy This role focuses on leveraging AI-driven automation tools like Google Apps Script, Gemini, and Claude Code to build self-service analytics tools for workforce strategy and operations within Capital One's Card Tech division. The primary goal is to enhance operational impact and provide sophisticated analytics for a large global workforce. | Data | 5 |
| Data Annotator The Emerging Technologies Enablement Team (ETE) performs data labeling tasks that support machine learning model and AI development within the Tech organization and across Capital One. This team plays a critical role in reviewing, evaluating, and annotating data to train AI models with the highest quality, accuracy, relevance, fluency, and compliance standards. | Data | 5 |
| Senior Quantitative Analyst - Global Finance This role focuses on quantitative analysis and modeling within Capital Markets & Analytics, applying machine learning and statistical methods to financial problems like derivatives and fixed income. It involves developing and enhancing analytical frameworks, creating novel solutions, and collaborating on cloud-based data solutions. The position requires expertise in quantitative methods, programming (Python/R/SQL), and communicating complex results. | Data | 5 |
| Senior Quantitative Analyst - Global Finance This role focuses on developing and enhancing quantitative models and analytical frameworks within Capital Markets & Analytics, leveraging machine learning and cloud technologies to manage financial risks and drive business insights in the fintech domain. The position requires expertise in quantitative analysis, statistical modeling, and programming, with a focus on applying these skills to financial markets, derivatives, and investment portfolios. | Data | 5 |
| Director, Data Scientist - External Data Strategy This role is for a Director of Data Science focused on External Data Strategy within Capital One's fintech domain. The position involves leading a team of 10-15 data scientists, building machine learning models and data pipelines, and leveraging technologies like Python, Spark, Databricks, and AWS. The primary focus is on data lifecycle management, from sourcing to feature engineering and model implementation, to understand customer financial lives and drive business decisions. The role requires strong leadership, technical expertise in data science and machine learning, and experience with large-scale data analysis and relational databases. | Data | 5 |