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 |
|---|---|---|
| Director, AI Engineering (Agentic AI Platform) Director of AI Engineering focused on building and managing an Agentic AI Platform. The role involves defining strategic vision, technical leadership for agentic workflows, overseeing the platform lifecycle, guiding technical teams, and ensuring scalability, reliability, and compliance. It requires strong leadership, technical expertise in AI/ML, and collaboration with cross-functional teams to deliver AI-powered products and foundational AI systems. | Agent | 8 |
| Senior Lead AI Engineer (Gen AI Platform Services) Senior Lead AI Engineer role focused on building and optimizing Gen AI platform services, including foundation model training, LLM inference, similarity search, guardrails, evaluation, and governance. The role involves designing, developing, testing, deploying, and supporting AI software components, leveraging cloud platforms and AI technologies, and optimizing performance for scalability, cost, latency, and throughput. | Serve |
| 8 |
| Distinguished AI Engineer Distinguished AI Engineer role focused on designing, developing, and deploying AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing LLM performance for scalability, cost, latency, and throughput in large-scale production AI systems, leveraging technologies like AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch. The candidate will contribute to the technical vision and roadmap of foundational AI systems. | ServePost-train | 8 |
| Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services) Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems at Capital One. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging AI technologies like AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch, and optimizing LLM performance for scalability, cost, latency, and throughput. | ServeAgent | 8 |
| Senior Lead AI Engineer(MLX, Agentic AI, Gen AI platform Services) Senior Lead AI Engineer responsible for 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 focuses on optimizing LLM performance for scalability, cost, latency, and throughput in production AI systems, leveraging technologies like AWS Ultraclusters, Huggingface, VectorDBs, and Nemo Guardrails. This role is part of the Intelligent Foundations and Experiences (IFX) team, aiming to advance AI science and engineering and deploy proprietary solutions. | ServeAgent | 8 |
| Senior Lead AI Engineer (LLM Gateway, FM Hosting) Senior Lead AI Engineer role focused on building and optimizing LLM inference infrastructure (Gateway, FM Hosting) and related AI components like similarity search, guardrails, evaluation, and observability for enterprise-scale AI products at Capital One. The role involves designing, developing, testing, deploying, and supporting these AI software components, with a strong emphasis on improving performance (scalability, cost, latency, throughput) of large-scale production AI systems. | ServeAgent | 8 |
| Lead AI Engineer (FM Hosting, LLM Inference) Lead AI Engineer focused on optimizing LLM inference for scalable, cost-effective production AI systems within an enterprise setting. The role involves designing, developing, and deploying AI software components, including foundation model training, inference, similarity search, guardrails, evaluation, and observability, leveraging various AI technologies and cloud platforms. | ServeAgent | 8 |
| Sr. Lead AI Engineer (GenAI Platform) Sr. Lead AI Engineer focused on building and scaling GenAI platforms, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. The role involves optimizing performance, cost, and latency of large-scale production AI systems using various open-source and cloud technologies. | ServeAgent | 8 |
| Senior Distinguished Engineer, AI Compute (Remote Eligible) Senior Distinguished Engineer focused on architecting and building the AI compute infrastructure for Capital One's enterprise machine learning platform. This role involves developing scalable, high-performance systems for diverse AI workloads including LLM pre-training, fine-tuning, inference, and agentic applications, leveraging distributed compute frameworks like Ray and Spark on cloud substrates. | ServePretrain | 8 |
| Senior Lead AI Engineer (Gen AI Platform Services, Agentic AI) Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems, including LLM inference, agentic AI, similarity search, guardrails, and model evaluation. The role involves optimizing performance, scalability, cost, and latency of large-scale production AI systems. | AgentServe | 8 |
| Distinguished AI Engineer (Remote) Distinguished AI Engineer responsible for 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 optimizing performance, scalability, cost, and latency of large-scale production AI systems, and contributing to the technical vision and roadmap of foundational AI systems. | ServeAgent | 8 |
| Lead Machine Learning Engineer (Gen AI, Python, Go, AWS) Lead Machine Learning Engineer focused on designing, building, and productionizing Generative AI applications and Agentic Workflow systems at scale. The role involves building robust ML serving architecture, developing high-performance code, and ensuring low latency and high availability of AI solutions, with a strong emphasis on cloud-native platforms and MLOps. | ServeAgent | 8 |
| Senior Manager, Data Science - LLM Customization Team Senior Manager of Data Science focused on LLM customization within Capital One's AI Foundations team. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like PyTorch, Hugging Face, LangChain, and VectorDBs. Responsibilities include adapting and fine-tuning LLMs for business applications, building NLP models through development phases, and operationalizing them in production systems. The ideal candidate has experience in training language models, expertise in areas like self-supervised learning or RLHF, and a track record of delivering models at scale. | Post-trainServe | 8 |
| Lead AI/ML Engineer (Platform, kubeflow) Lead AI/ML Engineer focused on building and optimizing AI platforms and infrastructure, including foundation model training, LLM inference, similarity search, guardrails, and evaluation. The role involves designing, developing, and deploying AI software components, leveraging various AI technologies, and improving the performance of large-scale production AI systems. | ServeAgent | 8 |
| Distinguished AI Engineer Distinguished AI Engineer role focused on designing, developing, and deploying AI software components including foundation model training, LLM inference, similarity search, guardrails, evaluation, and observability. The role involves optimizing performance, scalability, cost, and latency of large-scale production AI systems, leveraging cloud platforms and AI technologies. It requires a strong engineering and mathematics foundation, with experience in Python, Go, Scala, or Java, and cloud deployment. | ServeAgent | 8 |
| Lead AI Engineer (Gen AI Platform Services) Lead AI Engineer role focused on building and optimizing Gen AI Platform Services. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging various AI technologies and optimizing large-scale production AI systems for performance, scalability, cost, and latency. | ServeAgent | 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 next-generation customer experiences, leveraging technologies like Pytorch, AWS Ultraclusters, Huggingface, Lightning, and VectorDBs. Experience with training optimization, self-supervised learning, robustness, explainability, and RLHF is desired, with a track record of delivering models at scale. | Post-trainPretrain | 8 |
| Distinguished Engineer - Agentic AI Distinguished Engineer role focused on building agentic AI systems for real-time marketing and personalized sales within the enterprise banking domain. The role involves prototyping, defining technical strategy, and scaling these systems, with a focus on influencing architecture and evangelizing AI adoption. | Agent | 8 |
| Manager, Data Science - AI Software Engineering Manager of Data Science focused on AI Software Engineering, designing and building scalable AI architectures for the software development lifecycle using multi-agent solutions. The role involves partnering with cross-functional teams, leveraging technologies like Python, AWS, and Spark, and building ML models through all phases of development. Experience with agentic platforms, RAG, and advanced model customization is preferred. | AgentPost-train | 8 |
| Manager, Data Science - GenAI Digital Assistant Manager, Data Science role focused on GenAI for a digital assistant, involving research, development, fine-tuning LLMs, inference optimization, and multi-agentic workflows. Leverages Python, AWS, LangChain, LangGraph, HuggingFace, vLLM, and VectorDBs. Aims to improve customer experience through intelligent digital assistance. | AgentPost-train | 8 |
| Manager, Data Scientist - Recommendation & Personalization Systems Manager, Data Scientist role focused on building and deploying personalized recommendation engines using Foundation Models and Reinforcement Learning. The role involves partnering with cross-functional teams, leveraging technologies like Python and AWS, and building ML models through all phases of development. Expertise in Transformer-based architectures and scalable systems is required. | AgentPost-train | 8 |
| Senior Lead AI Engineer, AI Foundations This role focuses on designing, developing, testing, deploying, and supporting AI software components for foundational AI systems at Capital One. Key responsibilities include foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. The role also involves optimizing LLM performance for scalability, cost, latency, and throughput, leveraging technologies like AWS, Huggingface, VectorDBs, and PyTorch. The goal is to build and deploy proprietary AI solutions that deliver value to millions of customers and enhance products with AI capabilities. | ServeAgent | 8 |
| Lead AI Engineer, AI Foundations Lead AI Engineer focused on building and optimizing AI Foundations, including foundation model training, LLM inference, similarity search, guardrails, evaluation, governance, and observability. The role involves designing, developing, testing, deploying, and supporting AI software components, with a strong emphasis on improving performance (scalability, cost, latency, throughput) of large-scale production AI systems using state-of-the-art LLM optimization techniques. The role also touches on agentic systems through guardrails and similarity search, and model evaluation. | ServeAgent | 8 |
| Senior Lead AI Engineer (Gen AI Platform Services) Senior Lead AI Engineer role focused on building and scaling Gen AI Platform Services, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves optimizing AI systems for performance, cost, and latency, and contributing to the technical vision for foundational AI systems at Capital One. | ServeAgent | 8 |
| Applied Researcher I Applied Researcher I role focused on building AI foundation models and delivering AI-powered products, leveraging state-of-the-art AI developments for customer experiences. The role involves research, training, evaluation, and implementation of large deep learning models, with a focus on optimization, self-supervised learning, robustness, explainability, and RLHF. | Post-trainPretrain | 8 |
| Senior Lead AI Engineer Senior Lead AI Engineer responsible for 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 optimizing LLM performance for scalability, cost, latency, and throughput, and contributing to the technical vision and roadmap of foundational AI systems. The role leverages various AI technologies and requires strong engineering and mathematical foundations. | 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 optimizing LLM performance for scalability, cost, latency, and throughput, and contributing to the technical vision and roadmap of foundational AI systems. It 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 |
| Principal Associate, Data Scientist - LLM Customization Team Capital One is seeking a Principal Associate Data Scientist to join their LLM Customization Team. This role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch, Hugging Face, LangChain, and VectorDBs. The primary focus is on adapting and fine-tuning LLMs for business-specific applications, building NLP models through all phases of development, and operationalizing them in production systems. | Post-trainServe | 8 |
| Applied Researcher II (AI Foundations, LLM Core and Agentic AI) Applied Researcher II focused on AI Foundations, LLM Core, and Agentic AI at Capital One. The role involves partnering with cross-functional teams to deliver AI-powered products, leveraging technologies like Pytorch, AWS, Huggingface, and VectorDBs. Responsibilities include building AI foundation models through all development phases (design, training, evaluation, validation, implementation) and conducting high-impact applied research to improve customer experiences. The ideal candidate has a strong technical background, experience building large deep learning models, expertise in areas like training optimization, self-supervised learning, robustness, explainability, or RLHF, and a track record of delivering models at scale. Experience with LLM pre-training, optimization, or fine-tuning is highly preferred. | Post-trainAgent | 8 |
| Senior Manager, AI Engineering (People Leader) (Gen AI Platform Services) Senior Manager, AI Engineering (People Leader) for Gen AI Platform Services at Capital One. This role involves overseeing the design, development, testing, deployment, and support of AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The candidate will make build-vs-buy decisions, optimize LLM performance (scalability, cost, latency, throughput), contribute to the technical vision and roadmap of foundational AI systems, and lead/mentor an AI engineering team. Experience with cloud platforms and deploying scalable AI solutions is required. | ServePost-train | 8 |
| Manager, Product Management - AI Strategy & Enablement (Business Cards & Payments) Product Manager to execute technical AI vision, scale AI use cases, data infrastructure, development velocity, and knowledge governance. Design agentic workflows, evaluate LLM models, build agentic-first architectures, and connect AI to business goals. | AgentPost-train | 8 |
| Sr. Distinguished 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 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, Nemo Guardrails, and PyTorch. The role involves contributing to the technical vision and roadmap of foundational AI systems. | ServeAgent | 8 |
| Lead AI Engineer ( MLX, Gen AI Platform Services, Agentic AI) Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems at Capital One. 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 a broad stack of AI technologies and optimizing LLM performance for scalability, cost, and latency. | ServeAgent | 8 |
| Distinguished AI Engineer This role focuses on architecting and launching conversational AI experiences for millions of customers, involving foundation model training, LLM inference, and optimization of AI systems. It requires partnering with cross-functional teams to deliver AI-powered products and leveraging a broad stack of AI technologies. | 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 |
| Senior Lead AI Engineer (Gen AI Platform Services, Agentic AI) Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems, including LLM inference, optimization, and agentic AI platforms. The role involves designing, developing, testing, deploying, and supporting AI software components, leveraging various AI technologies, and contributing to the technical vision and roadmap. | ServeAgent | 8 |
| Sr. Lead AI Engineer (Gen AI Platform Services) This role focuses on engineering AI-powered products and platforms, specifically within Generative AI. Responsibilities include designing, developing, and supporting AI software components like foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role also involves optimizing LLM performance for scalability, cost, latency, and throughput, leveraging various AI technologies and cloud platforms. | ServeAgent | 8 |
| Sr. Distinguished Machine Learning Engineer (Remote-Eligible) This role focuses on building and scaling the intelligence and infrastructure for real-time, personalized customer experiences using ML and GenAI systems. It involves defining technical strategy, partnering with data science and ML platform teams, developing a rules engine, building ML infrastructure for end-to-end workflows, architecting low-latency event-driven systems, driving MLOps, and optimizing LLM performance for production AI systems. The role also involves providing technical leadership and leveraging various AI technologies. | AgentServe | 8 |
| Lead AI Engineer (AI Foundations) Lead AI Engineer focused on AI Foundations, responsible for designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, governance, and observability. The role involves optimizing large-scale production AI systems for performance (scalability, cost, latency, throughput) using various AI technologies and contributing to the technical vision and roadmap of foundational AI systems. | ServeAgent | 8 |
| Senior Lead AI Engineer,(MLX, Agentic AI, Gen AI platform Services) Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems at Capital One. Responsibilities include designing, developing, testing, deploying, and supporting AI software components like 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, and latency. | ServeAgent | 8 |
| Senior Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services) Senior Lead AI Engineer role focused on building and scaling Gen AI platform services, including foundation model training, LLM inference, similarity search, guardrails, and model evaluation. The role involves optimizing performance (scalability, cost, latency, throughput) of large-scale production AI systems and contributing to the technical vision for foundational AI systems. Requires strong engineering and AI expertise, with experience in cloud platforms and programming languages like Python. | ServeAgent | 8 |
| Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services) Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems, including LLM inference, similarity search, guardrails, and model evaluation, with an emphasis on optimizing performance and scalability for enterprise use. | ServeAgent | 8 |
| Senior Lead AI Engineer (FM Hosting, LLM Inference) Senior Lead AI Engineer focused on LLM inference and hosting infrastructure, optimizing performance, scalability, cost, and latency for large-scale production AI systems. The role involves designing, developing, and deploying AI software components, including foundation model training, inference, similarity search, guardrails, evaluation, governance, and observability, leveraging various AI technologies and cloud platforms. | ServeAgent | 8 |
| Sr. Lead AI Engineer (AI Foundations) This role focuses on engineering AI foundations, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, and optimization techniques for scalability, cost, latency, and throughput. It involves leveraging AI technologies and contributing to the technical vision and roadmap of foundational AI systems. | ServeAgent | 8 |
| Lead AI Engineer (AI Foundations) Lead AI Engineer focused on building and optimizing foundational AI systems, including LLM inference, similarity search, guardrails, and model evaluation, to enhance customer and associate experiences within a large enterprise. | ServeAgent | 8 |
| Director, Data Scientist - Generative AI Systems Capital One is seeking a Director, Data Scientist to lead the Generative AI Systems team. This role involves building and operationalizing AI-powered products, specifically focusing on LLMs for customer-facing applications in dialogue, summarization, comprehension, speech, and image processing. The position requires leading a team of specialists, experimenting with generative AI, and contributing to research. The role emphasizes partnering with cross-functional teams, leveraging technologies like PyTorch, AWS, Hugging Face, LangChain, and VectorDBs, and managing the full ML lifecycle from design to production for over 80 million customers. | AgentPost-train | 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 |
| Distinguished AI Engineer This role focuses on engineering and deploying AI-powered products and foundational AI systems, including large language model inference, optimization, and related components like similarity search and guardrails. The primary focus is on the serving and optimization of AI models in production, with a secondary involvement in agentic systems. | ServeAgent | 8 |
| Senior Distinguished AI Engineer Senior Distinguished 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 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 programming languages like Python, Go, Scala, or Java. | ServeAgent | 8 |
| Lead AI Engineer (MLX) Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing LLM performance for scalability, cost, latency, and throughput using various AI technologies and cloud platforms. | ServeAgent | 8 |