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 |
|---|---|---|
| Senior Lead AI Engineer (Gen AI Platform Services) This role focuses on engineering and optimizing AI software components, particularly large language model inference and related platform services, to improve performance, scalability, cost, and latency in a production environment. It involves designing, developing, testing, deploying, and supporting these components, leveraging various AI technologies and cloud platforms. | ServeAgent | 8 |
| Senior Manager AI Engineer (GenAI Platform Services) Senior Manager AI Engineer role focused on building and deploying GenAI Platform Services. Responsibilities include overseeing AI software components like foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves making build-vs-buy decisions, optimizing LLM performance, and contributing to the technical vision of foundational AI systems. Requires people leadership and experience in deploying scalable AI solutions on cloud platforms. |
| ServeAgent |
| 8 |
| Senior Lead AI Engineer (GenAI Platform Services) Senior Lead AI Engineer responsible for designing, developing, testing, deploying, and supporting AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing LLM performance for scalability, cost, and latency, and contributing to the technical vision and roadmap of foundational AI systems. | ServeAgent | 8 |
| Senior Lead AI Engineer (FM Hosting) This role focuses on designing, developing, testing, deploying, and supporting AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The engineer will invent and introduce state-of-the-art LLM optimization techniques to improve the performance of large-scale production AI systems and contribute to the technical vision and roadmap of foundational AI systems. The role involves leveraging various AI technologies and optimizing for scalability, cost, latency, and throughput. | ServeAgent | 8 |
| Lead AI Engineer (FM Hosting, LLM Inference) Lead AI Engineer focused on LLM inference and optimization for AI-powered products within a large enterprise. The role involves designing, developing, and deploying AI software components, with a strong emphasis on improving the performance, scalability, cost, and latency of production AI systems. | ServeAgent | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. 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 also requires inventing and introducing LLM optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems. The role leverages AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch. | ServeAgent | 8 |
| Sr. Lead AI Engineer This role focuses on designing, developing, testing, deploying, and supporting AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The engineer will also invent and introduce LLM optimization techniques to improve the performance (scalability, cost, latency, throughput) of large-scale production AI systems, leveraging technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails. The role is within the Intelligent Foundations and Experiences (IFX) team, aiming to advance AI science and engineering and deploy proprietary solutions. | ServeAgent | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer role focused on AI Foundations, LLM Core, and Agentic AI. Responsibilities include designing, developing, testing, deploying, and supporting AI software components like foundation model training, LLM inference, similarity search, guardrails, model evaluation, and governance. The role involves optimizing LLM performance for scalability, cost, and latency, and contributing to the technical vision for foundational AI systems. It requires experience with cloud platforms and AI/ML algorithms, particularly LLM inference, similarity search, vector databases, and guardrails. | ServeAgent | 8 |
| Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. Key responsibilities include optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and techniques. | ServeAgent | 8 |
| Senior Lead AI Engineer (FM Hosting, LLM Inference) Senior Lead AI Engineer focused on optimizing LLM inference performance, scalability, cost, and latency for production AI systems within Capital One's Intelligent Foundations and Experiences (IFX) team. The role involves designing, developing, and deploying AI software components, including foundation model training, inference, similarity search, guardrails, evaluation, and observability, leveraging cloud platforms and open-source AI technologies. | ServeAgent | 8 |
| Lead AI Engineer (FM Hosting, LLM Inference) Lead AI Engineer focused on optimizing LLM inference for scalability, cost, and latency within an enterprise AI setting. The role involves designing, developing, and deploying AI software components, including foundation model training, inference services, similarity search, guardrails, and model evaluation, leveraging cloud platforms and various AI technologies. | ServeAgent | 8 |
| Lead AI Engineer Lead AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging AI technologies and optimizing LLM performance for scalability, cost, latency, and throughput within an enterprise AI context. The position emphasizes building AI-powered products and foundational AI systems for millions of customers. | ServeAgent | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also includes optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and cloud platforms. The role emphasizes building responsible and reliable AI systems for banking applications. | ServeAgent | 8 |
| Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. It also includes optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and techniques. | ServeAgent | 8 |
| Senior Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Senior Lead AI Engineer focused on AI Foundations, LLM Core, and Agentic AI. The role involves designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. It also emphasizes inventing and introducing LLM optimization techniques to improve the performance of large-scale production AI systems. | ServeAgent | 8 |
| Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and evaluation. The role involves optimizing performance, scalability, cost, and latency of large-scale production AI systems using various AI technologies and cloud platforms. | ServeAgent | 8 |
| Sr. Lead Machine Learning Engineer Senior 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, informing ML infrastructure decisions, writing and testing code, automating tests and deployment, collaborating in Agile teams, retraining/maintaining/monitoring production models, leveraging cloud architectures, constructing data pipelines, and ensuring CI/CD best practices, code quality, risk governance, and Responsible AI. Requires experience in data-intensive solutions, programming, scaling ML systems, and leading ML development teams. | ServeData | 7 |
| Director, Data Science Director of Data Science at Capital One Canada, responsible for managing the risk and uncertainty in statistical models, leading the architecture and development of ML models through all phases, and leveraging technologies like Python and AWS, including agentic AI. The role involves managing talent and investigating new technologies for digital banking. | ServePost-train | 7 |
| Sr Lead Machine Learning Engineer This role focuses on productionizing and scaling machine learning applications and systems within a fintech domain. The engineer will be responsible for the design, development, deployment, and monitoring of ML models and infrastructure, with a strong emphasis on Python, Kubernetes, and cloud-based architectures. The role involves collaborating with data science and product teams, optimizing data pipelines, and ensuring the performance, availability, and responsible AI practices of ML systems. | ServeData | 7 |
| Sr. Lead Machine Learning Engineer Senior Lead Machine Learning Engineer responsible for productionizing ML applications and systems at scale, including designing, building, and delivering ML models and components, informing ML infrastructure decisions, writing and testing application code, automating tests and deployment, collaborating with cross-functional teams, retraining/maintaining/monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring CI/CD best practices, code management, risk governance, and Responsible AI. | ServeData | 7 |
| Sr. Lead Machine Learning Engineer Senior Lead Machine Learning Engineer responsible for productionizing ML applications and systems at scale, including designing, building, and delivering ML models and components, informing ML infrastructure decisions, writing and testing application code, automating tests and deployment, collaborating with cross-functional teams, retraining/maintaining/monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring CI/CD best practices, code management, risk governance, and Responsible AI. | ServeData | 7 |
| Senior Machine Learning Engineer (AI Foundations) Senior Machine Learning Engineer focused on building and productionizing ML models and components at scale within an enterprise AI context. The role involves designing, developing, and implementing ML applications, including LLMs and agentic systems, with a strong emphasis on infrastructure, operational efficiency, and responsible AI practices. | ServeData | 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, informing ML infrastructure decisions, writing and testing application code, collaborating with Agile teams, retraining/maintaining/monitoring production models, leveraging cloud architectures, constructing data pipelines, and ensuring code quality and model governance. Requires experience in data-intensive solutions, programming, and scaling ML systems. | ServeData | 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 |
| 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 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 |
| 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 |
| 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 |
| 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 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| Sr. Director, Cyber Technical (Cyber Hunt, Logging and Threat Detection) Senior Director role responsible for threat detection, cyber logging, privacy breach reporting, and threat hunting, with a focus on driving AI strategy for the cyber detection lifecycle and integrating AI/ML models for advanced threat detection and log management. | Serve | 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, informing ML infrastructure decisions, writing and testing code, automating tests and deployment, collaborating with cross-functional teams, retraining/maintaining/monitoring production models, leveraging cloud architectures, constructing data pipelines, and ensuring CI/CD best practices, code security, risk governance, and Responsible/Explainable AI. Requires experience in building, scaling, and optimizing ML systems and data-intensive solutions. | Serve | 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, informing ML infrastructure decisions, writing and testing application code, collaborating with Agile teams, retraining/maintaining/monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring CI/CD best practices. The role emphasizes building, scaling, and optimizing ML systems, with experience in Python/Scala/Java and distributed computing. | Serve | 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 models in production. The role emphasizes cloud-based architectures, data pipelines, CI/CD, and responsible AI practices. | Serve | 7 |
| Lead Machine Learning Engineer - (Bank Tech) 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 tests and deployment, retraining and monitoring models in production, leveraging cloud architectures, constructing data pipelines, and ensuring responsible AI practices. Requires experience in data-intensive solutions, programming, and building/scaling ML systems. | ServeData | 7 |
| Manager, Data Science - AI for Data Manager of Data Science focused on AI for Data within a financial services company. The role involves partnering with cross-functional teams to deliver AI-enabled features across the data lifecycle, building machine learning models from design through implementation, and leveraging technologies like Python, Spark, and AWS. Experience with NLP, Information Retrieval, Search, Recommendations, and LLM fine-tuning is preferred. | ServePost-train | 7 |
| Lead Machine Learning Engineer (Enterprise Platforms Technology) Lead Machine Learning Engineer responsible for productionizing ML applications and systems at scale, including designing, building, and delivering ML models, optimizing ML infrastructure, developing data pipelines, and maintaining models in production within a cloud-based environment. The role emphasizes engineering best practices for ML systems. | ServeData | 7 |
| Lead Machine Learning Engineer (Enterprise Platforms Technology) Lead Machine Learning Engineer focused on productionizing ML applications and systems at scale within an enterprise environment. Responsibilities include designing, building, and delivering ML models, optimizing ML infrastructure, writing and testing application code, automating tests and deployment, and maintaining models in production using cloud-based architectures and CI/CD best practices. | Serve | 7 |
| Lead Machine Learning Engineer (MLOps, KServe + building Kubernetes Clusters, PyTorch, TensorFlow on AWS) Lead Machine Learning Engineer focused on MLOps, building Kubernetes clusters, and deploying ML models at scale on AWS for a fintech company. The role involves designing, building, and maintaining ML infrastructure and pipelines, collaborating with data science and product teams, and ensuring the performance, reliability, and responsible deployment of ML systems. | Serve | 7 |
| Manager, Data Science Manager, Data Science role at Capital One in Plano, TX. This position involves partnering with cross-functional teams to deliver products, leveraging technologies like Python, AWS, and Spark. The core responsibilities include building machine learning models through all development phases (design, training, evaluation, validation, implementation) and translating complex work into business goals. Requires a quantitative background with experience in data analytics, machine learning, and relational databases. | Serve | 7 |
| Sr. Director, Product Management - AI/ML Platform Intelligence Sr. Director of Product Management to lead a team responsible for Capital One's Machine Learning and Generative AI platforms, focusing on core platform services for AI/ML that power business applications. Requires technical leadership, experience building products for data scientists and software developers, and familiarity with AI/ML infrastructure and tooling. | ServeAgent | 7 |
| Sr Lead Machine Learning Engineer This role focuses on the engineering aspects of machine learning, specifically in productionizing ML applications and systems at scale within a financial services context. The engineer will be involved in the design, development, implementation, and maintenance of ML models and infrastructure, ensuring high availability and performance. The role emphasizes collaboration, code quality, and leveraging cloud platforms for ML deployment. | Serve | 7 |
| Senior Associate, Data Science - Consumer Credit Risk Models and Data This role focuses on deploying, optimizing, and modernizing machine learning model pipelines and execution platforms for consumer credit risk management within a fintech company. The primary responsibility is to ensure these models are effectively implemented and provide insights for strategic decision-making, including loss allowances, stress testing, and capital allocation. | Serve | 7 |