Capital One
Banking · Banking
- HQ
- McLean, US
- Founded
- 1994
- Website
- capitalone.com
Banking · Banking
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 |
|---|---|---|
| Sr. Distinguished AI Engineer (Agentic AI Platform) Senior Distinguished AI Engineer focused on building and scaling an Agentic AI Platform at Capital One. The role involves contributing to platform architecture, standardizing agentic workflows using frameworks like LangGraph and AutoGen, developing GenAI SDKs/CLIs, implementing central guardrail services for trust and safety, optimizing orchestration for cost reduction, and driving innovation in areas like multimodal RAG and hierarchical agent memory. The role also includes coaching and evangelizing the platform vision. | Agent | 9 |
| Senior Director, Software Engineering - AI This role leads multiple teams of AI/ML software engineers to develop and manage enterprise LLM orchestration, generative AI pipelines, and low-latency inference microservices. It involves scaling production-grade ML systems and traditional architectures, mentoring engineers, and ensuring robust AI engineering practices for ethical deployment. |
| 8 |
| Manager, Data Science - GenAI Digital Assistant Manager, Data Science role focused on GenAI and conversational AI for a digital assistant, involving research, fine-tuning LLMs, inference optimization, and multi-agentic workflows within a fintech company. | AgentPost-train | 8 |
| Lead Machine Learning Engineer Lead Machine Learning Engineer at Capital One, focused on building and deploying AI-powered risk management solutions. The role involves designing, developing, testing, and deploying AI software components, including LLM inference, similarity search, guardrails, governance, observability, and agentic AI. Responsibilities include fine-tuning, developing, and evaluating ML and foundation models, contributing to technical vision, and leveraging a broad stack of AI technologies. The role also requires retraining, maintaining, and monitoring production models, constructing optimized data pipelines, and ensuring responsible and explainable AI practices. | AgentPost-train | 8 |
| Manager, Data Scientist - Recommendation & Personalization Systems Manager, Data Scientist role focused on building and deploying personalized recommendation engines using Foundation Models, Reinforcement Learning, and Transformer-based architectures for a large-scale fintech company. The role involves partnering with cross-functional teams, leveraging technologies like Python, AWS, and Spark, and building ML models through all phases of development. | AgentPost-train | 8 |
| Lead Machine Learning Engineer (Manager IC) Lead Machine Learning Engineer at Capital One's Risk Tech division, focusing on building and deploying AI-powered risk management solutions. The role involves designing, developing, testing, deploying, and supporting AI software components, including fine-tuning models, managing LLM inference, similarity search, guardrails, governance, observability, and agentic AI. Responsibilities include contributing to the technical roadmap, leveraging AI technologies, informing ML infrastructure decisions, maintaining production models, and constructing data pipelines, with an emphasis on Responsible and Explainable AI. | AgentPost-train | 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, 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 in production AI systems. | AgentServe | 8 |
| Lead AI Engineer (AI Foundations, LLM Core and Agentic AI) Lead AI Engineer role focused on building and optimizing AI systems, including foundation models, LLM inference, agentic AI, and related infrastructure. The role involves designing, developing, testing, deploying, and supporting AI software components, with a strong emphasis on improving performance, scalability, cost, and latency of large-scale production AI systems. It requires leveraging various AI technologies and contributing to the technical vision and roadmap for foundational AI systems. | AgentServe | 8 |
| Lead AI Engineer (GenAI Platform, AI Foundations, LLM Core and Agentic AI) Lead AI Engineer role focused on building and deploying GenAI platforms, LLM core, and agentic AI systems within an enterprise setting. Responsibilities include designing, developing, and supporting AI software components, optimizing LLM performance, and contributing to the technical vision for foundational AI systems. Requires experience with AI/ML algorithms, programming languages, and cloud platforms, with a focus on deploying scalable and responsible AI solutions. | AgentServe | 8 |
| 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, 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 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 - 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 (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 |
| 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 (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 |
| 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 |
| 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 |
| Senior Lead Software Engineer, Full Stack (Enterprise Platform Technology) This role focuses on building and operating AI-native software engineering harnesses, including agentic workflow orchestration systems, to enable governed AI model and coding agent delivery. It involves defining contracts, developing observability for AI-assisted workflows, integrating evaluation results into CI/CD, and building reusable APIs and services for AI-native engineering practices within an enterprise platform. | AgentEval Gate | 7 |
| Principal Associate, Data Scientist - People Strategy & Analytics Data Scientist role focused on applying AI/ML, specifically LLMs with RAG and prompt engineering, to HR talent decisions. The role involves building NLP and ML models through all development phases, partnering with cross-functional teams, and leveraging technologies like Python, SQL, AWS, LangChain, Hugging Face, VectorDBs, and Pytorch/TensorFlow. The ideal candidate is innovative, creative, technical, and statistically-minded. | AgentPost-train | 7 |
| Senior Associate, Data Scientist - People Strategy & Analytics Senior Associate, Data Scientist role focused on People Strategy & Analytics, applying AI/ML to talent decisions. Responsibilities include developing NLP and ML models, using LLMs with RAG and evaluation frameworks, partnering with cross-functional teams, and leveraging technologies like Python, SQL, AWS, LangChain, Hugging Face, and VectorDBs. The ideal candidate is innovative, creative, technical, and statistically-minded. | AgentPost-train | 7 |
| Data Analyst Manager - Model Risk Office Manager for a Data Analyst team focused on automating model risk management processes using AI and ML, including building conversational chatbots and multi-agent systems. The role involves optimizing data integration and driving strategy through analytics, with a strong emphasis on AI-powered automation. | AgentServe | 7 |
| Senior Lead Software Engineer, Full Stack Lead the design and implementation of AI-native software engineering harnesses that use approved models, coding agents, and developer workflows in governed control-plane capabilities. Build agentic workflow orchestration systems that support planning, code generation, validation, retry loops, human checkpoints, and controlled promotion through delivery environments. Define and implement typed input/output contracts, schemas, metadata capture, and workflow state models that make agentic execution auditable and repeatable. Develop trace capture, observability, and debugging capabilities for AI-assisted engineering workflows, including prompt/output lineage, tool-call traces, model/runtime metadata, and failure analysis. Integrate evaluation results into CI/CD and release workflows, including quality gates for fidelity, build correctness, accessibility, security, performance, and human-review outcomes. | AgentServe | 7 |
| Lead Machine Learning Engineer (Manager IC) Lead Machine Learning Engineer role focused on building and deploying AI-powered solutions for Risk management within Capital One. The role involves designing, developing, testing, and deploying AI software components, including LLM inference, similarity search, guardrails, and agentic AI. It also includes fine-tuning models, managing production models, and optimizing data pipelines, with a strong emphasis on responsible and explainable AI. | AgentServe | 7 |
| Lead Software Engineer, Full Stack Lead Software Engineer focused on building AI-native software engineering harnesses and agentic workflow orchestration systems for governed AI model and coding agent delivery within an enterprise environment. The role involves defining contracts, developing trace capture and observability, integrating evaluation results into CI/CD, and building reusable APIs and tooling to enable AI-native engineering practices. | AgentEval Gate | 7 |
| Senior Lead Machine Learning Engineer (Intelligent Foundations and Experiences) Senior Lead Machine Learning Engineer focused on building and scaling AI/ML capabilities for Credit and Financial Risk Management products. The role involves designing, building, and delivering AI-powered products, including LLM inference and agentic AI, and optimizing ML infrastructure and data pipelines for production at scale. | AgentServe | 7 |
| Business Manager - Supply Strategy & Intelligence This role focuses on building AI-powered orchestration workflows to identify, evaluate, and acquire vacation rental inventory for Capital One Travel. The Business Manager will define strategies, analyze customer search data, build competitive intelligence pipelines, and automate outreach to property owners, ultimately passing qualified leads to the Business Development team. | Agent | 7 |
| Manager, Product Management - Document Intelligence Product Manager role focused on leveraging GenAI and machine learning for automating document data extraction within an enterprise document management platform. The role involves defining the future of unstructured document data, deploying new experiences for agents and associates, and driving the enterprise scaling of extraction capabilities to decrease operational expenses and unlock new connections. The candidate will operate at the intersection of AI innovation, product data strategy, and enterprise-scale execution. | Agent | 7 |
| 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 Data Scientist - AI Foundations, Specialist Models The Entity Resolution Systems team builds and ships state-of-the-art machine learning solutions for entity resolution within the enterprise, impacting marketing and customer servicing. The role involves partnering with cross-functional teams to build a next-generation entity resolution solution using cutting-edge ML, including transformers and graph ML, and leveraging agentic AI tools and workflows. The ideal candidate is innovative, creative, technical, statistically-minded, and a data guru. | AgentPost-train | 7 |
| Lead Software Engineer, Full Stack-IC Lead Software Engineer to architect and launch conversational AI experiences for millions of Capital One customers, leveraging Generative AI capabilities. The role involves leading a team, developing cloud-based solutions, and collaborating with product managers. | Agent | 7 |
| Senior Lead Software Engineer (Golang + EKS, Kubernetes, LLM's + Agentic flows + control/data planes) Senior Lead Software Engineer role focused on building platforms for AI/ML solutions at scale within Capital One's Machine Learning Experience Team (MLX Tech). The role involves leading development teams, collaborating on cloud-based solutions, and leveraging technologies like Golang, EKS, Kubernetes, LLMs, and agentic workflows to implement AI/ML for customer assistance in a financial context. | Agent | 7 |
| Lead Data Engineer - HR Tech Lead Data Engineer role focused on HR Tech, involving the design, development, and implementation of technical solutions. The role specifically mentions building and deploying GenAI and Agentic AI solutions, indicating a focus on developing AI-powered systems. | Agent | 7 |
| Director, 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 |
| 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 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 |