Capital One
Banking · Banking
- HQ
- McLean, US
- Founded
- 1994
- Website
- capitalone.com
Banking · Banking
Currently tracking 241 active AI roles, down 22% 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 |
|---|---|---|
| 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 |
| Senior Lead Machine Learning Engineer Senior Lead Machine Learning Engineer at Capital One, focusing on productionizing ML applications and systems at scale. Responsibilities include designing, building, and delivering ML models and components, informing ML infrastructure decisions, writing and testing application code, automating tests and deployment, collaborating in Agile teams, retraining/maintaining/monitoring production models, leveraging cloud architectures, constructing data pipelines, implementing CI/CD best practices, and ensuring code security, model governance, and Responsible/Explainable AI. The role requires significant experience in building, scaling, and optimizing ML systems and leading teams. | Serve | 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 |
| Lead Machine Learning Engineer Lead Machine Learning Engineer role focused on productionizing ML applications and systems at scale within a fintech company. Responsibilities include designing, building, and delivering ML models and components, informing ML infrastructure decisions, writing and testing application code, automating tests and deployment, retraining and monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring code quality, model governance, and responsible AI practices. Requires experience in designing data-intensive solutions, programming, and building/scaling ML systems. | Serve | 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 |
| Staff Software Engineer - Machine Learning Staff Software Engineer - Machine Learning role at Capital One in London. This role focuses on owning and driving the ML/AI technical strategy for UK use cases, leading ML engineering efforts across multiple teams, and providing technical consultancy. It involves defining best practices, driving MLOps standards, and collaborating with data science and enterprise platform teams. The role requires deep expertise in Python, ML engineering, MLOps, cloud-native architectures, ML frameworks, and Gen AI/Agentic frameworks like LangGraph, LangChain, VectorDBs, and RAG. Experience in designing and scaling low-latency, customer-facing ML/AI architectures and understanding responsible AI practices are also key. | AgentServe | 7 |
| Senior Manager, Product Management - AI Orchestration & Experiences Senior Product Manager to lead the experience layer for Associate Assist, defining complex orchestration logic for AI tools to work seamlessly together. The role requires moving AI Agent architectures from Proof of Concept to Production at scale and designing stateful agent workflows. | Agent | 7 |
| Manager, Product Management Product Management role focused on AI/ML Model Governance within the Machine Learning Experience (MLX) team at Capital One India. The role involves developing product vision and strategy, understanding needs of data scientists and ML engineers, partnering with leadership, and managing product backlogs in an Agile environment. Experience in building Enterprise AI/ML platform products or AI/ML powered products for enterprises is required. | Ship | 7 |
| Principal Associate, Data Science This role is in Model Risk Management for Retail Banking, focusing on independent validation and technical challenge of state-of-the-art models, including ML and Generative AI, for domains like Fraud, Deposits, and Generative AI. The role involves partnering with developers, building tools for model evaluation, and communicating complex findings. It requires strong statistical and ML knowledge, experience with Python/R, and ideally, experience in financial services, Fraud, or Generative AI. | ShipEval Gate | 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 |
| Senior Associate, Data Scientist - People Strategy & Analytics This role focuses on applying AI and ML to HR talent strategy, building models for understanding associate behavior and improving HR efficiency. It involves developing NLP and ML models using prompt engineering, RAG, and evaluation frameworks, leveraging technologies like Python, SQL, AWS, LangChain, Hugging Face, and VectorDBs. The candidate will partner with cross-functional teams to deliver HR tools and AI-powered products, translating complex data science work into business outcomes. | AgentPost-train | 7 |
| Manager, Product Management Product Management role focused on AI/ML Model Governance within the Machine Learning Experience (MLX) team at Capital One India. The role involves developing product strategy, understanding needs of data scientists and ML engineers, partnering with leadership, and managing product backlogs for enterprise AI/ML platform products, with a focus on responsible GenAI and ML model deployment. | Ship | 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 |
| Machine Learning Engineering - Intelligent Foundations and Experiences (IFX) Machine Learning Engineer focused on productionizing ML models and systems at scale within a fintech company. Responsibilities include designing, building, and delivering ML models, informing ML infrastructure decisions, writing and testing code, automating tests and deployment, retraining/maintaining/monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring code quality and model governance. The role emphasizes experience with ML frameworks, productionizing models, and cloud-based ML systems. | ServeData | 7 |
| Lead Data Scientist (Model Developer) / Deep Learning Practitioner Lead Data Scientist role focused on developing and deploying deep learning models for underwriting capabilities in a fintech company. The role involves advancing existing models, building neural networks, transforming multi-modal inputs, and driving projects from prototype to production. Requires experience in sequential data, model development leadership, and modern ML frameworks. | Post-trainServe | 7 |
| Manager, Data Scientist - US Card DFS Acquisitions Manager, Data Scientist role focused on building and deploying machine learning models for credit card customer acquisitions in the fintech domain. The role involves the full model lifecycle, from design and training to evaluation, validation, and implementation, with a focus on delivering customer-facing products. | ShipPost-train | 7 |
| Data Scientist / Statistician (Model Developer) Develop and maintain machine learning models for underwriting in the financial services market, focusing on feature engineering, insight generation, and handling various data types including sequential and multi-modal data. Requires strong statistics, ML, Python, and Model Risk Management experience. | Post-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 |
| Lead Software Engineer Lead Software Engineer for the Machine Learning eXperience (MLX) team at Capital One India. This role focuses on building and deploying responsible GenAI and ML models, educating associates on AI platforms, driving innovation, and integrating AI into company products. The role involves leading technology projects, partnering with product/design, collaborating across Agile teams, developing features, sharing technical knowledge, and debugging distributed systems. Requires extensive experience in software engineering, backend services, databases, technical leadership, data-intensive solutions, SDKs, and deploying ML platform solutions in the cloud. Preferred qualifications include MLOps, production-ready capabilities, responsible AI implementation, and exposure to Generative AI, LLMs, LangChain, and vector databases. | ServeAgent | 7 |
| Manager, Data Scientist - Bureau Data Strategy Capital One is seeking a Manager, Data Scientist for their Bureau Data Strategy team. This role involves partnering with cross-functional teams to deliver products, leveraging technologies like Python, AWS, and Spark to analyze large datasets, and building machine learning models through all phases of development. The ideal candidate is customer-focused, a leader, technically proficient with open-source tools and cloud platforms, and skilled in data analysis. | Post-train | 7 |
| Principal Data Scientist - Banking Payments Capital One is seeking a Principal Data Scientist to build machine learning models for bank operations, focusing on payment channels, anomaly detection, and operational streamlining with agentic processes. The role involves leveraging Python, Snowflake, and various ML technologies including LLMs and transformer architectures. | AgentPost-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 architecting and productionizing intelligent systems for Capital One Travel's luxury market. The role involves designing, building, and delivering ML models and components, informing ML infrastructure decisions, writing and testing application code, automating tests and deployment, and leveraging cloud-based architectures to deliver optimized ML models at scale. Responsibilities include retraining, maintaining, and monitoring models in production, constructing data pipelines, and ensuring adherence to CI/CD, Responsible AI, and Explainable AI best 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 |
| Principal Associate, Data Scientist, SBB Fraud Data Scientist role focused on building and deploying machine learning models for fraud detection in the Small Business Bank (SBB) at Capital One. The role involves working with large datasets, applying various ML techniques, and collaborating with cross-functional teams to protect customers and the company from financial fraud. | Post-train | 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 Machine Learning Engineer Senior Machine Learning Engineer at Capital One focused on productionizing ML applications and systems at scale. Responsibilities include designing, building, and delivering ML models, informing ML infrastructure decisions, writing and testing code, automating tests and deployment, retraining/maintaining/monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring code quality and model governance. Requires experience with ML frameworks, productionizing models, and cloud-based ML systems. | Serve | 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 |
| Senior Lead Machine Learning Engineer Senior Lead Machine Learning Engineer role 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 tests and deployment, and maintaining models in production using cloud-based architectures and CI/CD best practices. The role also involves constructing data pipelines and ensuring responsible AI practices. | 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 |