Capital One
Banking · Banking
- HQ
- McLean, US
- Founded
- 1994
- Website
- capitalone.com
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).
Currently tracking 241 active AI roles, down 26% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $123k–$392k (avg $231k).
Banking · Banking
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.
What leadership said about AI on earnings calls (above the line, stacked by event type) vs how many AI roles the company actually posted (below the line). Each side scales to its own peak — read shape, not absolute height.
Trajectory events (left half, cyan) vs active AI roles posted (right half, slate), bucketed by stage. Darker cell = more activity for this company.
Management confirmed ongoing investment in building AI infrastructure and specific AI experiences.
“We continue to invest in building AI infrastructure and specific AI experiences.”— Richard D. Fairbank
Management reaffirmed the long-term technology transformation strategy, emphasizing the architecture's capability to handle big data and AI in real-time.
“We are in the 14th year of our technology transformation from the bottom of the tech stack up. This has involved going 100% into the cloud, building a modern data ecosystem and rebuilding the company in modern technology platforms that can handle big data and AI in real time.”— Richard D. Fairbank
CEO Richard Fairbank articulated the strategic value of embedding AI into the company's existing ecosystem rather than treating it as a standalone feature.
“All companies will be able to take advantage of AI, but the leverage is vastly greater when AI is embedded in the company's ecosystem.”— Richard D. Fairbank
Finalized the acquisition of Brex, with the rationale of leveraging Capital One's data and AI assets to drive growth in business payments.
Fairbank described the vision for the combined Capital One and Brex platform as an integrated system for business payments and banking, powered by a modern tech stack built for AI.
“An integrated platform that combines business payments, spend management, and banking powered by a modern tech stack that's built for and powered by AI.”— Richard Fairbank
CEO Richard Fairbank stated that the company's technology infrastructure was designed with the AI revolution in mind and that they are actively building AI solutions across their business lines.
“Our tech stack was built from the outset working backwards from the AI revolution and we are now building AI solutions across our businesses.”— Richard Fairbank
Capital One announced the acquisition of Brex, citing the company's modern tech stack and in-house AI agents for expense management, audit, and future procurement/accounting capabilities as a core strategic rationale.
“This automated platform is the foundation for AI solutions on top of Brex has built and deployed their own in-house AI agents for expense management and audit. And are on the way to procurement payments, and accounting agents.”— Richard Fairbank
Management confirmed that incremental investment levels in AI and AI talent have risen relative to previous periods to advance market position.
CEO Richard Fairbank identified AI-driven experiences as a new competitive front for the company.
“And a new front in this battle will be AI driven experiences We are gearing up for that.”— Richard D. Fairbank
CEO Richard Fairbank outlined the strategy of embedding AI into the core of the business model, including operations, risk management, and customer experiences.
“Transforming the business model of banking with AI. Requires AI to be deeply embedded in the technology operations, processes, risk management, and customer experiences of the company.”— Richard D. Fairbank
CEO Richard Fairbank emphasized that significant investment in AI and AI talent is required to capitalize on growth opportunities.
“These opportunities require significant investment in AI and AI talent, and we are doing that.”— Richard D. Fairbank
CEO Richard Fairbank articulated the company's AI strategy, emphasizing that Capital One's modern tech stack and data investment position it to reinvent business models by putting AI at the heart of operations, risk management, and customer experience.
“But only the companies built on a modern tech stack and deeply invested in data will be in a position to reinvent their business model to put AI at the heart of operations, risk management, and the customer experience.”— Richard Fairbank