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 |
|---|---|---|
| Applied Researcher II Applied Researcher II at Capital One focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to push AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires experience building large deep learning models and delivering models at scale. | Post-trainServe | 8 |
| Applied Researcher I Applied Researcher I at Capital One focused on building AI foundation models and delivering them at scale for customer-facing products. The role involves partnering with cross-functional teams, leveraging various technologies, and conducting applied research to push AI capabilities into next-generation customer experiences. Requires a strong technical background in deep learning, model training, optimization, and a track record of delivering models in production. |
| Post-trainPretrain |
| 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, inventing LLM optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems, and contributing to the technical vision and roadmap of foundational AI systems. Requires strong engineering and mathematics foundation, expertise in hardware, software, and AI, and experience with cloud platforms and AI/ML algorithms. | ServeAgent | 8 |
| Senior Lead AI Engineer Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems within an enterprise setting. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. The role emphasizes optimizing LLM performance for scalability, cost, latency, and throughput, and contributing to the technical vision and roadmap of foundational AI systems. | ServeAgent | 8 |
| Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration) Lead AI Engineer role focused on building and scaling Gen AI platforms, agentic AI systems, and LLM infrastructure. The role involves designing, developing, and deploying AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. It emphasizes optimizing LLM performance for scalability, cost, latency, and throughput, and leveraging a broad stack of AI technologies. | AgentServe | 8 |
| Senior Lead AI Engineer Senior 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 inventing and introducing state-of-the-art LLM optimization techniques to improve the performance of large-scale production AI systems, leveraging technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails. This position is key to bringing AI capabilities to life at Capital One, empowering teams across the company and delivering value to millions of customers. | ServeAgent | 8 |
| Applied Researcher II (AI Foundations) Applied Researcher II focused on AI Foundations at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting applied research to integrate AI advancements into customer experiences. The ideal candidate has a deep understanding of AI methodologies, experience building large deep learning models, and a track record of delivering models at scale. | PretrainPost-train | 8 |
| Applied Researcher I Applied Researcher I role focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to push the latest AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires a PhD or MS with experience in AI/ML, with expertise in areas like training optimization, self-supervised learning, robustness, explainability, or RLHF, and a track record of delivering models at scale. | Post-trainPretrain | 8 |
| 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, experimentation, governance, and observability. It also emphasizes optimizing LLM performance for scalability, cost, and latency in production AI systems. | ServePost-train | 8 |
| Applied Researcher I Applied Researcher I role focused on building AI foundation models, engaging in applied research to push AI developments into customer experiences, and delivering models at scale. Requires experience in training optimization, self-supervised learning, robustness, explainability, or RLHF, with a track record of delivering libraries or platform code. | Post-trainPretrain | 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 in production AI systems within an enterprise setting. | ServeAgent | 8 |
| Lead AI Engineer Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems within a fintech company. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability. The role emphasizes optimizing LLM performance (scalability, cost, latency, throughput) and contributing to the technical vision and roadmap for AI systems. Requires experience with AI/ML algorithms, programming languages like Python, and cloud platforms, with a focus on deploying scalable and responsible AI solutions. | ServeAgent | 8 |
| Applied Researcher II (AI Foundations) Applied Researcher II focused on AI Foundations at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting applied research to integrate AI advancements into customer experiences. Requires a deep understanding of AI methodologies, experience building large deep learning models (language, images, events, graphs), and expertise in areas like training optimization, self-supervised learning, robustness, explainability, or RLHF. A track record of delivering models at scale and contributing to research through publications or projects is essential. | PretrainPost-train | 8 |
| Applied Researcher I Applied Researcher I role focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to push state-of-the-art AI into customer experiences, with a strong emphasis on delivering models at scale and potentially contributing to publications. | Post-trainPretrain | 8 |
| Applied Researcher II Applied Researcher II at Capital One focused on building AI foundation models and delivering them at scale for customer-facing products. The role involves partnering with cross-functional teams, leveraging technologies like Pytorch and VectorDBs, and engaging in applied research to push AI capabilities. | Post-trainPretrain | 8 |
| Applied Researcher I Applied Researcher I role focused on building AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. The role involves high-impact applied research to push the latest AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires a PhD or MS with experience in AI/ML, with expertise in areas like training optimization, self-supervised learning, robustness, explainability, or RLHF, and a track record of delivering models at scale. | Post-trainPretrain | 8 |
| Applied Researcher I (AI Foundations) Applied Researcher focused on building AI foundation models from design through training, evaluation, validation, and implementation. The role involves applied research to push AI developments into customer experiences, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Requires experience building large deep learning models and delivering models at scale. | PretrainPost-train | 8 |
| Applied Researcher II Applied Researcher II at Capital One focused on partnering with cross-functional teams to deliver AI-powered products. The role involves leveraging technologies like Pytorch and VectorDBs, building AI foundation models through all development phases, and engaging in applied research to advance customer experiences. Requires a deep understanding of AI methodologies, experience building large deep learning models, and a track record of delivering models at scale. | Post-trainPretrain | 8 |
| Distinguished AI Engineer (Agentic AI Platform) The role is for a Distinguished AI Engineer focused on building an enterprise Generative AI Platform. The engineer will design the agentic workflow framework, shared services (memory, guardrails, vector search, SDKs), and blueprints to enable product teams to compose AI capabilities. Key responsibilities include evaluating agentic frameworks, developing an end-to-end GenAI SDK/CLI, implementing central guardrail services, optimizing orchestration for performance, and mentoring other engineers. The role emphasizes creating scalable, safe, and explainable AI solutions for millions of users. | AgentServe | 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 focuses on optimizing LLM performance (scalability, cost, latency, throughput) for production AI systems and contributing to the technical vision and roadmap of foundational AI systems. | AgentServe | 8 |
| 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 |
| Sr Distinguished Engineer Capital One is seeking a Sr. Distinguished Engineer to lead the development and scaling of agentic AI systems for business card marketing, underwriting, and sales. The role involves defining technical strategy, hands-on prototyping, and influencing enterprise architecture to create hyper-personalized marketing systems, assistive technologies, and autonomous sales agents. | Agent | 8 |
| Distinguished Engineer Distinguished Engineer role focused on building and scaling agentic AI systems for marketing and sales within an enterprise context. Responsibilities include prototyping, defining technical strategy, influencing architecture, and mentoring teams, with a focus on real-time, hyper-personalized customer engagement and assistive technologies for sales teams. | Agent | 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 (Gen AI Platform Services, Agentic AI) Senior Lead AI Engineer role focused on building and deploying Gen AI platform services, including agentic AI systems. Responsibilities span foundation model training, LLM inference, similarity search, guardrails, evaluation, experimentation, governance, and observability, leveraging technologies like AWS, Huggingface, VectorDBs, and Nemo Guardrails. The role emphasizes optimizing large-scale production AI systems for performance, cost, and latency, and contributing to the technical vision and roadmap for foundational AI systems. | AgentServe | 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 |
| 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 model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms. | AgentServe | 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 (LLM Customization and Finetuning) Senior Lead AI Engineer focused on 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, experimentation, governance, and observability. It requires leveraging AI technologies like Huggingface, VectorDBs, and PyTorch, and optimizing LLM performance for scalability, cost, latency, and throughput in production AI systems. The candidate should have a strong engineering and mathematics foundation, experience with cloud platforms, and the ability to lead and mentor teams. | Post-trainServe | 8 |
| Applied Researcher I (Multi-agent Systems, Knowledge Graphs/GraphRAG/Graph-of-Thought / GoT, MCP, LangGraph, Agent Protocols) Applied Researcher focused on building multi-agent AI systems, leveraging knowledge graphs, GraphRAG, Graph-of-Thought, LangGraph, and agent protocols to transform the software development lifecycle. The role involves applied research, model development, and delivering AI-powered products. | Agent | 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 |
| 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 such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, and agentic systems. The role involves optimizing LLM performance for scalability, cost, and latency, and contributing to the technical vision and roadmap for foundational AI systems. Requires strong engineering and mathematics foundation, expertise in Python/Go/Scala/Java, and experience with cloud platforms and AI technologies like Huggingface, VectorDBs, and PyTorch. | AgentServe | 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 model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms. | AgentServe | 8 |
| Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services) Lead AI Engineer role focused on building and deploying AI-powered products, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails, and optimizing LLM performance for scalability, cost, and latency. The position requires a strong engineering foundation and experience in AI/ML algorithm development and deployment on cloud platforms. | AgentServe | 8 |
| Director, AI Engineering Director of AI Engineering responsible for the strategic vision, development, and management of autonomous AI systems and platforms, with a focus on agentic workflows and ensuring compliance with regulations and ethical AI best practices within a fintech domain. | Agent | 8 |
| Principal Associate, Data Scientist - LLM Customization Team Capital One's LLM Customization team is seeking a Principal Associate Data Scientist to work on GenAI models. The role involves creating high-quality data for training and testing, building capabilities for evaluating and monitoring generative models, and developing horizontal capabilities like search, summarization, RAG, and agentic workflows for production applications. The candidate will partner with cross-functional teams, leverage technologies like Pytorch, AWS, Hugging Face, LangChain, and VectorDBs, and adapt/finetune LLMs for customer-facing applications. Responsibilities include building ML and NLP models through all development phases, from design to evaluation and validation, and operationalizing them in production systems serving over 80 million customers. Experience in training language models, explainability, RLHF, and delivering models at scale is required. | DataPost-train | 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 focuses on optimizing LLM performance (scalability, cost, latency, throughput) for production AI systems and contributing to the technical vision and roadmap of foundational AI systems. | AgentServe | 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 focuses on optimizing LLM performance (scalability, cost, latency, throughput) for production AI systems and contributing to the technical vision and roadmap of foundational AI systems. | AgentServe | 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 Manager, Data Scientist - US Card (Generative AI Systems) Senior Manager, Data Scientist for the Generative AI Systems (Genesis) team within Capital One's US Card division. This role focuses on building and delivering state-of-the-art generative AI-based solutions for various applications including dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series modeling. The goal is to enhance both internal business efficiency and customer-facing experiences. The role involves partnering with cross-functional teams, leveraging a broad tech stack, and building ML models through all phases of development. | ShipPost-train | 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 |