Capital One
Banking · Banking
- HQ
- McLean, US
- Founded
- 1994
- Website
- capitalone.com
Banking · Banking
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 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.
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 |
|---|---|---|
| Distinguished Engineer Distinguished Engineer role focused on architecting and leading the evolution of content generation, storage, and retrieval platforms at scale, integrating AI to empower marketers within a regulated fintech environment. The role involves defining technical direction, prototyping, and collaborating with product and AI teams, with a strong emphasis on LLM systems, RAG, and prompt tooling. | Agent | 7 |
| Lead Software Engineer Lead Software Engineer to build an AI-powered marketing content layer, integrating LLMs into content generation, channel-specific builds, and AI-assisted compliance workflows. The role involves developing multi-agent orchestration systems for content review and dispatch, building evaluation and observability tooling for LLM outputs, and defining guardrail frameworks. | AgentPost-train |
| 7 |
| Distinguished Engineer (Messaging & Marketing Technology) Distinguished Engineer role focused on architecting and leading the end-to-end execution of AI applications, specifically an agentic orchestration system for marketing technology. The role involves scaling from MVP to a sophisticated system, leveraging a diverse data ecosystem including vector stores, and driving engineering excellence with Gen AI coding tools. | Agent | 7 |
| Lead Software Engineer, Full Stack (Enterprise Platforms Technology) Lead Software Engineer to build an AI-powered marketing content layer, integrating LLMs into content generation, channel-specific builds, and AI-assisted compliance workflows. The role involves developing multi-agent orchestration systems for content review and dispatch, and building evaluation/observability tooling for LLM outputs. | AgentEval Gate | 7 |
| Distinguished Engineer (Messaging & Marketing Technology) Distinguished Engineer role focused on architecting and leading the end-to-end execution of AI applications, specifically an agentic orchestration system for marketing technology. The role involves scaling from MVP to a sophisticated system, leveraging a diverse data ecosystem including vector stores, and driving engineering excellence with Gen AI coding tools. | Agent | 7 |
| Senior Manager, Data Science - Financial Services Senior Manager, Data Science role at Capital One focused on building Generative AI models and products for financial services. The role involves partnering with cross-functional teams, leveraging technologies like Python and AWS, and working across the full development lifecycle from design to monitoring. Emphasis on LLM prompting/fine-tuning and GenAI application development. | AgentPost-train | 7 |
| Manager, Data Scientist - Recommendation & Personalization Systems Manager, Data Scientist focused on Recommendation & Personalization Systems within an Applied AI team. The role involves architecting and deploying personalized recommendation engines using Foundation Models, Reinforcement Learning, and Transformer-based architectures. It operates at the intersection of research and real-world impact, dealing with high-scale ML models and billions of customer records in the fintech domain. | AgentPost-train | 7 |