Capital One

AI Engineer

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components, including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Leverage open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch
• Invent and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput
• Contribute to the technical vision and long-term roadmap of foundational AI systems
• Own end-to-end architecture for complex AI systems, ensuring maintainability, observability, and ethical alignment
• Define and maintain SLOs for AI reliability, including latency, uptime, and model performance drift
• Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines
• Lead cross-functional technical reviews for AI system deployments, ensuring security, data governance, and compliance standards
• Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation

AI Engineer 4 – AI Foundations, LLM Customization, Finetuning, Reinforcement Learning

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Leverage open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch
• Invent and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput
• Contribute to the technical vision and long-term roadmap of foundational AI systems
• Design, implement, and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models
• Establish and lead cost-performance governance reviews tracking GPU utilization, model throughput, and inference cost efficiency
• Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards
• Mentor Principal- and Manager-level AI engineers and elevate organizational technical maturity

AI Engineer 5 – SDKs: Gen AI Evaluation, MCP

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Leverage open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch
• Invent and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput of production AI systems
• Contribute to the technical vision and long-term roadmap of foundational AI systems
• Design, implement, and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models
• Establish and lead cost-performance governance reviews tracking GPU utilization, model throughput, and inference cost efficiency
• Lead design councils or design review boards to ensure technical consistency and compliance with AI engineering standards
• Mentor Principal- and Manager-level AI engineers and elevate organizational technical maturity

AI Engineer 5 – Gen AI Platform Services, Agentic AI, Guardrails, Evaluation

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Leverage open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch
• Invent and introduce foundation model optimization techniques to improve scalability, cost, latency, and throughput
• Contribute to the technical vision and long-term roadmap of foundational AI systems
• Own end-to-end architecture for complex AI systems, ensuring maintainability, observability, and ethical alignment
• Define and maintain service-level objectives for AI reliability, including latency, uptime, and model performance drift
• Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines
• Lead technical reviews for AI system deployments, ensuring security, data governance, and compliance standards
• Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation

AI Engineer 4 – Gen AI Platform Services, Agentic AI, Agent Guardrails, Agent Evaluation, Agent Memory

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Leverage Open Source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch
• Invent and introduce foundation model optimization techniques to improve scalability, cost, latency, and throughput of production AI systems
• Contribute to the technical vision and long-term roadmap of foundational AI systems
• Design, implement, and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models
• Establish and lead cost-performance governance reviews, tracking GPU utilization, model throughput, and inference cost efficiency
• Lead team design councils or design review boards for technical consistency and AI engineering standards compliance
• Mentor Principal- and Manager-level AI engineers and foster cross-domain learning

AI Engineer 5 – AI Foundations, LLM Customization, Finetuning, Reinforcement Learning

Data Analyst

• Mine complex, voluminous, and varied data sources and platforms using open-source and digital technologies
• Build well-managed data solutions, tools, and capabilities enabling self-service frameworks for data consumers
• Explore and quickly grasp new technologies to progress varied initiatives
• Partner with the business to provide consultancy and translate business needs into tools, techniques, metrics, and dashboards
• Drive analysis that provides meaningful insights on business strategies
• Drive understanding and adherence to data quality management principles, including metadata, lineage, and business definitions
• Collaborate with Tech teams to manage security mechanisms and data access governance
• Build and execute tools to monitor and report on data quality
• Help drive Capital One’s AI automation strategy for Card Data using LLM tools such as Gemini and Claude
• Automate complex data validation processes and establish proactive metrics to eliminate operational fire drills

Principal Data Analyst – Card Data AI Automation

• Lead a talented analytics team to drive the AI automation strategy for Card Data
• Champion LLM tools such as Gemini and Claude to automate complex data validation processes
• Establish proactive metrics to eliminate operational fire drills
• Design scalable, well-governed AI solutions
• Foster a supportive and high-performing team culture
• Refine an enterprise-wide analytical tools validation framework
• Plan and execute validation projects
• Assess the quality and risk of analytical tool methodologies and tool usage processes across Capital One
• Understand technical issues in analytical tools and assess tool risks and opportunities
• Research, identify, and prototype industry best practices for emerging analytical tools
• Communicate results through validation reports, presentations, and verbal communication
• Leverage education, colleagues, and training opportunities to develop solutions to business problems
• Coach and mentor junior staff

Senior Manager, Data Analysis – Card Data AI Automation

Product Manager

• Lead the line and balance transfer teams, including 4–6 direct reports and partnerships with multiple technology teams
• Deliver high-leverage capabilities and updates critical to evolving the business
• Define and refine the vision for the next-generation platform supporting line strategies
• Recruit, coach, and develop product team members
• Ensure the business area is well-managed and audit- and customer-ready
• Reimagine product solutions around internal and external customer needs
• Deliver outcomes through leverage and execution excellence
• Leverage technology for innovative and resilient solutions
• Identify and resolve complex problems while mitigating product risks
• Lead cross-functional teams and drive organizational alignment

Director, Product Management – Customer Management Platform Lead

Product Designer

• Lead a team of Learning Experience Designers
• Build comprehensive learning ecosystems supporting product management, technical, data, and specialized line-of-business teams
• Translate complex business requirements into intuitive, engaging, and measurable learning content
• Oversee a diverse portfolio of learning initiatives
• Partner with strategic advisors, business leaders, program leads, and HR partners
• Mentor designers in creating eLearnings, instructor-led training, workbooks, and digital platforms
• Infuse artificial intelligence tools into creative and operational workflows
• Develop the skills of direct reports and establish learning design excellence standards
• Use a product mindset to iterate and improve learning based on user insights, engagement analytics, and business outcomes
• Own intake and prioritization of learning design initiatives
• Create project roadmaps aligned with business impact
• Translate complex product, technical, and specialized business concepts into tailored learning solutions
• Build infrastructure ensuring consistent learning design output and organizational guideline compliance

Manager, Learning Experience Design

Project Manager

• Partner with leadership to design and refine long-term labor strategy
• Ensure organizational structures, capacity planning, and talent deployment align with strategic priorities
• Advocate for the employee journey by designing rituals, feedback loops, and governance frameworks
• Establish operational rhythms, management standards, and meeting structures across teams
• Eliminate friction, sharpen decision-making, and ensure accountability
• Translate high-level business goals into scalable operational guidelines
• Advise senior technology leaders on high-stakes proposals and strategic vision
• Partner with Finance, HR, and Labor to align technology priorities with broader business outcomes
• Build strong business partnerships and perform critical thinking, problem solving, and complex analysis
• Develop executive-ready presentations and compelling data-driven narratives

Senior Director, Project Management – Bank Tech

Operations

• Own logistics, operations, and delivery for Enterprise Onboarding on-site and virtual events
• Own staffing and scheduling for major Enterprise Onboarding events, including on-site staff and virtual facilitator management
• Manage room bookings, space setup, catering, and on-site logistics with GWS and local site contacts
• Partner with Hiring Logistics to receive and review weekly lists of new hires
• Partner with Associate Experience Technology to ensure materials, technology, and supplies are prepared and available
• Oversee weekly delivery of new-hire onboarding and troubleshoot real-time issues
• Identify and recommend improvements to enhance the onboarding experience
• Manage the shared onboarding inbox and provide timely, consistent responses to new-hire inquiries
• Partner with the Customer Success Lead and Program Manager on communications for associates and people leaders
• Own the team budget, including tracking and auditing on a regular cadence
• Manage the team’s well-managed arm, including monthly newsletters, Google Drive organization, and documentation
• Support ad-hoc horizontal initiatives across the team

Associate – Horizontal Operations, Enterprise Onboarding

• Steer the strategic vision for how Capital One manages relationships with millions of customers
• Drive innovation and strategy for customer management platforms
• Refine work for multiple platform projects supporting enterprise-wide innovation initiatives
• Help shape a potential complete rebuild of customer management technology ecosystems
• Deliver technology ecosystems that provide customers with the right offers and experiences
• Lead cross-functional teams to solve customer problems and drive organizational alignment
• Apply human-centered, business-focused, technology-driven, integrated problem-solving, and transformational leadership practices

Director, Product Management – Customer Management Platform Strategy Lead

Risk

• Serve as a key risk thought partner for new businesses and emerging payments activities
• Evaluate AI capabilities, smart automation, and advanced analytics to modernize the payments risk landscape
• Document payments use cases and support lines of business in demonstrating adherence to payment risk policies and standards
• Identify opportunities to deploy RPA, natural language processing, and predictive risk analytics
• Streamline manual governance and oversight, operationalize controls, and improve monitoring efficiency
• Partner with Accountable Executives, Product, Technology, and Business Risk Offices
• Assess strategy, operations, and risks across ACH, wire, card, and real-time payment types throughout the payment lifecycle
• Drive risk mitigation across strategic and emerging payments initiatives across the enterprise
• Build and define risk modernization approaches for new businesses and payment programs

Risk Manager – Payments Risk Integration, Strategy, and Modernization

• Lead a true greenfield initiative to build an enterprise-scale product from the ground up
• Design and deliver a first-of-its-kind third-party management system
• Redefine how Capital One operates across its entire third-party network
• Reimagine the status quo and identify value creation opportunities
• Drive innovative and sustainable customer experiences through technology
• Lead cross-functional teams to solve customer problems and drive organizational alignment
• Apply the Product Framework across human-centered, business-focused, technology-driven, integrated problem-solving, and transformational leadership dimensions

Senior Director, Product Management – Enterprise Services, Supplier Product, Risk, Operations

• Lead a greenfield initiative to build an enterprise-scale product from the ground up
• Design and deliver a third-party management system across Capital One's network
• Manage holistic relationships between Capital One and key third parties
• Reimagine and innovate product solutions around internal and external customer needs
• Deliver business outcomes through leverage and execution excellence
• Leverage technology to deliver innovative and resilient solutions
• Identify and resolve complex problems while mitigating product risks
• Lead cross-functional teams and drive organizational alignment