Capital One
Banking · Banking
- HQ
- McLean, US
- Founded
- 1994
- Website
- capitalone.com
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.
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 |
|---|---|---|
| Machine Learning Engineer (AI Foundations) Machine Learning Engineer focused on productionizing AI/ML applications and systems at scale within a fintech company. The role involves designing, building, and delivering ML models and components, informing ML infrastructure decisions, writing and testing application code, and collaborating in an Agile team. Responsibilities include retraining, maintaining, and monitoring models in production, leveraging cloud-based architectures, constructing data pipelines, and ensuring CI/CD best practices, code security, and responsible AI. Basic qualifications include a Bachelor's degree and experience in data-intensive solutions and programming. Preferred qualifications include cloud experience, open-source contributions, and building production-ready data pipelines. | ShipServe | 7 |
| Senior Lead Machine Learning Engineer (Intelligent Foundations and Experiences) |
| AgentServe |
| 7 |
| Manager, Data Scientist, Travel Intelligence, Flights Manager, Data Scientist for Capital One Travel's Flights domain, focusing on building in-house machine learning solutions to create personalized and seamless customer experiences. The role involves end-to-end technical strategy, model development, and leveraging large datasets for fintech product innovation in the travel space. | ShipServe | 7 |
| Manager, Data Scientist - Innovation Hub Manager of Data Scientists focused on designing and deploying generative AI and AI-powered capabilities within a financial services company. The role involves building ML models through all development phases, leveraging various technologies, and translating complex work into business goals. It emphasizes innovation, creativity, leadership, and technical expertise in data science and machine learning. | ShipPost-train | 7 |
| Senior Associate, Product Manager, Card Intelligence Product Manager role focused on leveraging Machine Learning and Generative AI within the Card Intelligence division to build products for fraud prevention, aiming to reduce time-to-market for ML models and improve customer lifecycle management. | Ship | 7 |
| Business Manager - Supply Strategy & Intelligence This role focuses on building AI-powered orchestration workflows to identify, evaluate, and acquire vacation rental inventory for Capital One Travel. The Business Manager will define strategies, analyze customer search data, build competitive intelligence pipelines, and automate outreach to property owners, ultimately passing qualified leads to the Business Development team. | Agent | 7 |
| Senior Manager, Data Science - Anti-Money Laundering Modeling and Advanced Data Insights Capital One is seeking a Senior Manager of Data Science to lead the Anti-Money Laundering (AML) Modeling and Advanced Data Insights team. This role involves modernizing AML identification processes using advanced analytics, statistics, and machine learning. The team develops predictive models, monitoring dashboards, and reporting, with end-to-end responsibility for production models. The role requires partnering with cross-functional teams, leveraging technologies like Python, AWS, and Spark, and building ML models through all development phases. | Post-train | 7 |
| Manager, Data Science - Consumer Identity Machine Learning Manager of Data Science focused on Consumer Identity Machine Learning within Capital One's AI foundation organization. The role involves building and operationalizing real-time, personalized ML models for customer experiences, fraud prevention, and data accuracy, serving over 50 million customers. It requires working across the data science lifecycle, from design and training to evaluation and productionization, in a regulated fintech environment. | Post-trainServe | 7 |
| Senior Manager, Data Science - Model Risk Office Senior Manager, Data Science for Capital One's Model Risk Office, focusing on evaluating risk for Card Fraud models. The role involves building challenger models using advanced algorithms and providing mentorship. This is a management role within a fintech domain, focused on the application and risk assessment of AI/ML models in a production environment. | ShipPost-train | 7 |
| Manager, Product Management - Document Intelligence Product Manager role focused on leveraging GenAI and machine learning for automating document data extraction within an enterprise document management platform. The role involves defining the future of unstructured document data, deploying new experiences for agents and associates, and driving the enterprise scaling of extraction capabilities to decrease operational expenses and unlock new connections. The candidate will operate at the intersection of AI innovation, product data strategy, and enterprise-scale execution. | Agent | 7 |
| Lead AI Engineer Lead AI Engineer role focused on designing, developing, and deploying AI-powered products and foundational AI systems. The role involves working with LLM inference, similarity search, guardrails, model evaluation, and optimization techniques to improve scalability, cost, and latency of production AI systems. It requires strong engineering and AI expertise, with a focus on building and scaling AI solutions within an enterprise context. | ServeAgent | 7 |
| Lead Machine Learning Engineer Lead Machine Learning Engineer at Capital One focused on productionizing ML applications and systems at scale. Responsibilities include designing, building, and delivering ML models, optimizing ML infrastructure, writing and testing code, automating tests and deployment, and maintaining/monitoring models in production. The role also involves constructing data pipelines and leveraging cloud-based architectures. | ServeData | 7 |
| Senior Manager, Product Manager, AI Acceleration Product Manager role focused on AI Acceleration within Capital One, leading cross-functional teams to deliver customer-facing AI solutions. The role involves shaping product strategy, working with engineers and data scientists, and understanding language models and generative AI to improve customer and associate experiences. It requires blending human-centered needs with technical understanding of LLMs and designing AI agents. | ShipAgent | 7 |
| Manager, Data Science - Model Risk Office Manager for a Model Validation team within the Model Risk Office, responsible for validating payment network business models (fraud, AML, counterparty risk, financial models) in accordance with regulatory guidance and internal policies. The role involves assessing statistical and machine learning models, communicating technical concepts to diverse stakeholders, and leveraging open-source technologies for continuous improvement. | Ship | 7 |
| Lead Software Engineer Lead Software Engineer for the MLX team, focused on building and deploying responsible GenAI and ML models, onboarding associates to GenAI/ML platforms, driving innovation, and integrating Generative AI/ML into the company's fabric. The role involves full-stack development, distributed microservices, observability, and AWS ML platform solutions. | ServeAgent | 7 |
| Senior Associate, Data Scientist - US Card (Resiliency Intelligence) This role focuses on building and implementing supervised and reinforcement learning models to predict customer needs and recommend optimal financial solutions for customers facing hardship. The models directly impact millions of customers and the business's income, requiring development through all phases from design to implementation in production environments. | Post-train | 7 |
| Senior Director, Data Science - Head of Fair Lending Analytics - Fair & Responsible Banking Compliance Senior Director of Data Science to lead the Fair Lending Analytics group within Capital One's Compliance and Ethics Department. This role involves leading a team of data scientists and analysts to identify and mitigate fair lending and compliance risks, conduct data analyses of lending decisions, and provide guidance on business activities. The position requires strong leadership, technical expertise in data science and machine learning, and experience in developing and implementing fair lending and responsible data use processes, particularly in the context of AI in credit. | ShipPost-train | 7 |
| Manager, Data Scientist - US Card (Resiliency Intelligence) Capital One is seeking a Manager, Data Scientist for their US Card Resiliency Intelligence team. This role focuses on building machine learning models using supervised and reinforcement learning to predict customer needs and recommend personalized solutions for financial stability. The team uses Python, XGBoost, scikit-learn, and statsmodels, deploying models that impact millions of customers daily in both analytical and production environments. The ideal candidate is creative, technical, statistically-minded, and proficient with large datasets and open-source tools. | Post-train | 7 |
| Manager, Product Management - GenAI Transformation (Business Cards & Payments) Product Manager to support the AI transformation for Capital One's Field Sales Organization. The role focuses on enabling GenAI-powered experiences by designing and building a horizontal foundation for shared, trusted context for AI applications, centralizing and standardizing data for downstream AI systems. The role also owns the end-to-end feedback loop strategy for continuous improvement of AI model performance and retraining. | Agent | 7 |
| Principal Associate, Data Scientist - Retail Bank Valuations Data Science This role focuses on building and implementing next-generation customer valuation models for the Retail Bank to improve marketing efficiency and drive account growth. It involves data and model pipelining, machine learning, and model operations using Python and ML libraries. | Post-train | 7 |
| Principal Data Scientist - AI Foundations, Specialist Models The Entity Resolution Systems team builds and ships state-of-the-art machine learning solutions for entity resolution within the enterprise, impacting marketing and customer servicing. The role involves partnering with cross-functional teams to build a next-generation entity resolution solution using cutting-edge ML, including transformers and graph ML, and leveraging agentic AI tools and workflows. The ideal candidate is innovative, creative, technical, statistically-minded, and a data guru. | AgentPost-train | 7 |
| Lead Software Engineer, Full Stack-IC Lead Software Engineer to architect and launch conversational AI experiences for millions of Capital One customers, leveraging Generative AI capabilities. The role involves leading a team, developing cloud-based solutions, and collaborating with product managers. | Agent | 7 |
| Senior Lead Software Engineer (Golang + EKS, Kubernetes, LLM's + Agentic flows + control/data planes) Senior Lead Software Engineer role focused on building platforms for AI/ML solutions at scale within Capital One's Machine Learning Experience Team (MLX Tech). The role involves leading development teams, collaborating on cloud-based solutions, and leveraging technologies like Golang, EKS, Kubernetes, LLMs, and agentic workflows to implement AI/ML for customer assistance in a financial context. | Agent | 7 |
| Lead Data Engineer - HR Tech Lead Data Engineer role focused on HR Tech, involving the design, development, and implementation of technical solutions. The role specifically mentions building and deploying GenAI and Agentic AI solutions, indicating a focus on developing AI-powered systems. | Agent | 7 |
| Director Product Management (AI and Automation) Product Management Director focused on AI and Automation within Capital One's Finance ecosystem. The role involves identifying and launching AI features, designing automated workflows, managing the model lifecycle, ensuring responsible AI innovation with guardrails, and using AI metrics for iteration. The goal is to transition Finance from manual processes to automated, scalable solutions. | ShipAgent | 7 |
| Distinguished Engineer Distinguished Engineer role focused on defining and delivering the next evolution of engineering within People Tech, shifting from domain-centric to a system-driven model. The role involves advancing Engineering and Operational Excellence, reducing duplication, and enabling faster, more reliable delivery through standardized execution and reuse. Responsibilities include articulating technical vision, decomposing complex problems, ensuring quality, serving as an expert on non-functional characteristics, mentoring, and architecting high-scale, reusable capabilities. Requires experience in designing and building distributed AI/ML systems and cloud computing. | Serve | 7 |
| Director, Software Engineering Director of Software Engineering at Capital One, leading teams to build AI-based marketing applications, focusing on an automated agentic flow for campaign creation and management. The role involves mentoring engineers, collaborating with product managers, and improving software engineering practices within an Agile and AWS environment. Key technologies include Python, Java, Vue.js, Postgres, Dynamo DB, and vector stores like Milvus. | Agent | 7 |
| Principal Associate, Data Scientist - Retail Bank Data Scientist role focused on building machine learning models for retail banking operations, including time series forecasting and optimization, with an emphasis on interpretable outputs. The role involves the full ML lifecycle from design to implementation and works with large volumes of data. | Post-train | 7 |
| Senior Manager, Data Scientist - Travel Intelligence Senior Manager, Data Scientist for Capital One's Travel Intelligence team, focusing on the Hotels domain. The role involves owning the end-to-end technical strategy for Search & Sort and Pricing Optimization, moving from offline models to real-time ML solutions. Responsibilities include partnering with cross-functional teams, leveraging technologies like Python and AWS, and building ML models through all development phases. | Post-train | 7 |
| Lead AI Engineer (AI Foundations, LLM Customization and Finetuning) Lead AI Engineer focused on AI Foundations, LLM Customization and Finetuning within Capital One's Intelligent Foundations and Experiences (IFX) team. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. It requires leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and inventing optimization techniques for performance, scalability, cost, latency, and throughput of large-scale production AI systems. The role also contributes to the technical vision and roadmap of foundational AI systems. | ServePost-train | 7 |
| Senior Manager, Data Science - Credit Review This role focuses on building and challenging existing statistical and machine learning models within the credit review domain at Capital One. The Senior Manager will lead a team, leverage technologies like Python, AWS, and Spark, and partner with cross-functional teams to deliver data-driven solutions that impact risk management and enterprise outcomes. The role requires strong technical and statistical skills, with experience in model building, validation, and various ML techniques. | Post-train | 7 |
| Senior Manager, Data Science - Model Risk Office Senior Manager for Model Risk Office at Capital One, focusing on identifying and quantifying risks associated with models, including Generative AI. The role involves building ML models to challenge existing production models and contributing to the governance framework for future models. It requires validating models across various business domains and communicating risks to executives. The ideal candidate is innovative, creative, a leader, technically proficient, statistically minded, and skilled in handling large datasets. | ShipPost-train | 7 |
| Senior Lead Machine Learning Engineer Senior Lead Machine Learning Engineer at Capital One, focused on productionizing ML applications and systems at scale within a fintech domain. Responsibilities include designing, building, and delivering ML models, optimizing ML infrastructure, writing and testing code, automating deployment, and maintaining models in production. The role involves leveraging cloud platforms, constructing data pipelines, and ensuring responsible AI practices. | ShipServe | 7 |
| Lead Machine Learning Engineer Lead Machine Learning Engineer at Capital One, focused on productionizing ML applications and systems at scale. Responsibilities include designing, building, and delivering ML models, developing ML infrastructure, writing and testing code, automating tests and deployment, and leveraging cloud-based architectures. The role emphasizes CI/CD, responsible AI, and optimized data pipelines for ML models. | Serve | 7 |
| Lead Machine Learning Engineer Lead Machine Learning Engineer at Capital One, focused on productionizing ML applications and systems at scale within an Agile team. Responsibilities include designing, building, and delivering ML models, informing infrastructure decisions, writing and testing code, automating tests and deployment, retraining/maintaining/monitoring production models, leveraging cloud architectures, constructing data pipelines, and ensuring code quality, model governance, and adherence to Responsible and Explainable AI best practices. | Ship | 7 |
| Manager, Data Scientist - Credit Review Capital One is seeking a Manager, Data Scientist for their Credit Review Models, Data and Innovative solutions team. The role involves building statistical and machine learning models to challenge existing production models, leveraging technologies like Python, AWS, and Spark. The candidate will partner with cross-functional teams to deliver innovative solutions in risk management and enterprise decision-making. The role requires a strong statistical background, experience with machine learning, and proficiency in open-source tools and cloud platforms. | Post-train | 7 |
| Senior Associate, Data Scientist - US Card (Applied GenAI) This role focuses on applying generative AI and LLMs to unstructured data (text, image) for enterprise applications in areas like customer servicing and document processing. It involves building and operationalizing ML/NLP models, assessing production architectures, defining AI observability, and evaluating AI system behavior. The role emphasizes practical application and scaling AI adoption within a regulated financial environment. | AgentServe | 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, evaluation/observability tooling, and guardrail frameworks for LLM outputs, with a focus on enterprise AI applications. | AgentEval Gate | 7 |
| Lead AI Engineer (AI Foundations, LLM Customization and Finetuning) Lead AI Engineer focused on AI Foundations, LLM Customization and Finetuning within Capital One's Intelligent Foundations and Experiences (IFX) team. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. It requires leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and inventing optimization techniques for performance, scalability, cost, latency, and throughput of large-scale production AI systems. The role also contributes to the technical vision and roadmap of foundational AI systems. | ServePost-train | 7 |
| Senior Associate, Data Scientist - Corporate Strategy This role focuses on building machine learning models for corporate strategy within a financial services company. It involves leveraging data science skills to analyze consumer behavior, market conditions, and peer performance, and translating complex work into tangible business goals. The role requires experience across the full ML development lifecycle, from design through implementation, using technologies like Python, AWS, and Spark. | Post-train | 7 |
| Distinguished Engineer - Software Engineering Distinguished Engineer role focused on building an AI-powered platform for business process automation and intelligent finance, with a strong emphasis on agentic patterns and real-time observability. The role involves technical leadership, strategy, and hands-on contribution to complex problems in a regulated fintech environment. | Agent | 7 |
| Senior Manager, Machine Learning Engineering Senior Manager, Machine Learning Engineering at Capital One, focused on productionizing ML applications and systems at scale within a fintech domain. The role involves designing, building, and delivering ML models, managing ML infrastructure, optimizing data pipelines, and ensuring the performance and availability of ML applications in production. It requires people management experience and collaboration with cross-functional Agile teams. | ShipServe | 7 |
| Sr. Lead, Machine Learning Engineer (Enterprise Platforms Technology) Senior Machine Learning Engineer focused on building, scaling, and optimizing ML systems and applications within enterprise platforms. Responsibilities include designing, developing, and deploying ML models, constructing data pipelines, and ensuring high availability and performance of ML applications using cloud-based architectures and CI/CD best practices. | Serve | 7 |
| Sr Director, Software Engineer - Card Tech AI Seeking a Senior Director of Software Engineering to lead a team in redefining software development speed and quality using AI-native workflows and agentic development tools. The role involves a 'Player-Coach' approach, shipping production code, mentoring engineers, and ensuring AI-generated output is flawless, secure, and scalable. The focus is on bridging the gap between Intent and Execution (I=E) through rigorous, spec-driven design. | Agent | 7 |
| Director, Software Engineer - Card Tech AI Seeking a Director of Software Engineering to lead a team in redefining software development speed and quality using AI-native workflows and agentic development tools. The role involves a 'Player-Coach' approach, shipping production-ready code, mentoring engineers, and ensuring AI-generated output is flawless, secure, and scalable. | Ship | 7 |
| Director, Software Engineer - Card Tech AI Seeking a Director of Software Engineering to lead a team in redefining software development speed and quality using AI-native workflows and agentic development tools. The role involves a 'Player-Coach' approach, shipping production-ready code, mentoring engineers, and ensuring AI-generated output is flawless, secure, and scalable. | Ship | 7 |
| Distinguished Software Engineer - IFX This role is for a Distinguished Software Engineer focused on building and scaling the foundational compute infrastructure for an enterprise AI+ML platform. The engineer will work on distributed systems, cloud technologies, and support various AI/ML workloads including LLM pre-training, fine-tuning, inference, and agentic applications. | ServePretrain | 7 |
| Senior Associate, Data Scientist - Audit Data Science This role focuses on building and implementing ML and NLP models, including LLM-based chatbots and GenAI applications, within the fintech domain for audit and risk management. The position involves the full ML lifecycle from design to productionization and monitoring, leveraging various technologies like Python, Hugging Face, LangChain, and AWS. | Post-trainServe | 7 |
| Principal Associate, Data Scientist - Anti-Money Laundering This role focuses on building and deploying AI/ML models for Anti-Money Laundering (AML) within a financial services context. The responsibilities include developing production-ready pipelines, building ML models and AI tools, and specifically fine-tuning, evaluating, and productionizing LLMs. The role involves working with technologies like Python, AWS, Spark, and LLM-specific tools such as LangGraph and LlamaIndex, with a strong emphasis on delivering industry-leading risk management products. | AgentPost-train | 7 |
| Manager, Data Scientist Manager, Data Scientist role focused on model risk management within a fintech company. The role involves partnering with cross-functional teams to identify and quantify model risks, building ML models to challenge existing production models, contributing to model governance, and validating various models. Requires strong statistical and data science skills, experience with ML, and open-source tools. | ShipPost-train | 7 |