Capital One

Operations

• Lead delivery for high-priority strategic initiatives
• Lead a team improving frontline handling of complex digital call types
• Support issue triage and readiness for large-scale Retail Bank initiatives
• Establish a closed-loop feedback channel between operations and partner teams
• Drive organizational change by owning and improving scalable systems and processes for strategic planning and OKR execution
• Lead medium- to large-scale complex projects and provide strategic direction in a matrixed environment
• Partner cross-functionally with operations, product, technology, and other stakeholders
• Communicate across all organizational levels and elevate key decision points to leadership
• Design, develop, and manage project plans in a complex, dynamic environment
• Ensure programs and initiatives are appropriately documented to mitigate risk and support on-time delivery
• Identify pain points and provide insights leading to enhancements

Manager, Process Manager – Bank Voice Servicing

Data Scientist

• Partner with data scientists, software engineers, and product managers to deliver customer-focused products
• Use Python, Conda, AWS, H2O, Spark, and other technologies to analyze large volumes of numeric and textual data
• Build machine learning models through design, training, evaluation, validation, and implementation
• Build a robust scoring platform and deploy models
• Create innovative analytical tools and leverage alternative data sources
• Collaborate cross-functionally with engineering and product teams
• Scale products, valuation models, and analytical capabilities
• Translate complex data science work into tangible business goals
• Research and evaluate emerging technologies and state-of-the-art methods
• Support credit decisioning, cash flow underwriting, and real-time credit analytics

Senior Associate, Data Scientist – Credit Card Innovation

Communications

• Develop and implement executive communications strategies that bring business imperatives to life
• Serve as a trusted communications partner to senior executives and leadership teams
• Provide real-time counsel on reputation, engagement, and change management
• Plan and prepare internal communications, narratives, key messages, and announcements
• Create executive-led meetings, digital/video assets, presentations, and special events
• Highlight tangible wins, lessons learned, and evidence of progress
• Balance strategic planning with tactical execution and deliver results
• Operate autonomously and proactively to push projects across the finish line
• Evaluate communications performance using data and metrics
• Recommend adjustments to communications strategies, messaging, and channels based on feedback

Commercial Executive Communications Manager

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, 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, vector databases, 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
• 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 review boards to ensure technical consistency and compliance with AI engineering standards
• Mentor Principal- and Manager-level AI engineers and foster cross-domain learning

Human Resources

• Partner with HR leaders and colleagues to drive and deliver HR strategic priorities
• Drive the operating rhythm of HR leadership teams
• Design agendas for executive meetings that drive outcomes and accelerate decision-making
• Support the drafting and evolution of the multi-year HR strategy
• Define and manage metrics, reporting on key objectives and organizational health
• Provide data-driven insights to help leaders pivot or persevere
• Draft executive communications, including framing, pre-reads, and actionable discussion syntheses
• Bridge high-level strategy and enterprise-wide execution of HR objectives
• Design culture initiatives fostering engagement and high performance
• Identify and pilot responsible AI integration into strategic operations workflows
• Improve efficiency in data synthesis, reporting, and team process optimization
• Manage complex, cross-functional initiatives and influence senior leaders

Manager, HR Strategic Operations

Artificial Intelligence

• Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products
• Leverage PyTorch, AWS Ultraclusters, Hugging Face, Lightning, and other technologies to analyze large volumes of numeric and textual data
• Build AI foundation models through design, training, evaluation, validation, and implementation
• Conduct applied research to advance AI developments into next-generation customer experiences
• Translate complex research into tangible business goals
• Collaborate with senior researchers on internal technical reports or conference submissions summarizing novel methods or findings
• Apply AI and machine learning to improve customer experiences and banking products at Capital One

Applied Researcher 4 – AI Foundations, LLM Core, Agentic AI

Strategy

• Drive strategy and execute high-priority projects for Capital One
• Partner with HR leaders and colleagues to deliver HR strategic priorities
• Design agendas for executive meetings to drive outcomes and accelerate decision-making
• Support the drafting and evolution of the multi-year HR strategy
• Define and own organizational health and key-objective metrics
• Manage reporting and provide data-driven insights to HR leaders
• Draft executive communications, including framing materials and pre-reads
• Synthesize complex discussions into actionable outcomes
• Help design initiatives fostering engagement and high performance within Strategic Operations and HR
• Identify and pilot responsible AI integration into strategic operations workflows
• Drive efficiency in data synthesis, reporting, and team process optimization

Principal Associate, HR Strategic Operations

• Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products
• Leverage PyTorch, AWS Ultraclusters, Hugging Face, Lightning, and other technologies to analyze numeric and textual data
• Build AI foundation models through design, training, evaluation, validation, and implementation
• Conduct applied research to advance AI developments into next-generation customer experiences
• Translate complex research into tangible business goals
• Lead cross-functional research threads bridging prototype model development and deployment with ML engineering partners
• Ensure scientific insights translate into production impact

Applied Researcher 5, AI Foundations, LLM Core, Agentic AI

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
• Oversee design, development, testing, deployment, and support of AI software components
• Work across foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Make build-versus-buy decisions across open-source and SaaS AI technologies
• Develop foundation-model optimization techniques to improve scalability, cost, latency, and throughput
• Contribute to the technical vision and long-term roadmap for foundational AI systems
• Attract and retain AI talent and support team members’ personal and professional development
• Translate enterprise AI goals into team roadmaps with measurable outcomes and regular readouts
• Operationalize Responsible AI through review gates, documentation and evaluation requirements, and rollout/rollback standards
• Create collaboration interfaces with Research, Data, and Platform teams to accelerate the model lifecycle

Senior Manager, AI Engineer – 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 of production AI systems
• Contribute to the technical vision and long-term roadmap for 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 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 – AI Foundations, LLM Core, Agentic AI

Compliance

• Provide advice and effective challenge on compliance risks impacting network and merchant businesses
• Develop expert-level understanding of network and merchant business processes
• Analyze business processes and determine applicability of laws and regulations using Capital One’s global legal inventory
• Identify trends in business data and assess network payments compliance risks, including emerging external risks
• Maintain subject matter expertise in the broader payments industry and applicable laws, rules, and regulations
• Collaborate with first- and second-line functions to analyze the risk management program framework and its applicability to network and merchant services
• Educate and influence risk management colleagues and senior leaders on nuanced or specialized considerations
• Ensure ongoing application of compliance requirements to business expansions, new products, downstream entities, card acceptance opportunities, and new products
• Develop relationships with Business Risk, Legal, and Audit peers to support network compliance integration
• Provide compliance advisory support to the PULSE Network, a leading US Debit Network and Global ATM Network

Senior Manager, Compliance Advisory – Network Compliance

• 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 large-scale 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 to ensure technical consistency and compliance with AI engineering standards
• Mentor Principal- and Manager-level AI engineers and foster cross-domain learning

AI Engineer 5, MLX, Agentic AI, Gen AI platform Services

• 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 including 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 design councils or review boards to ensure technical consistency and compliance with AI engineering standards
• Mentor Principal- and Manager-level AI engineers and elevate organizational technical maturity

• 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 including 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 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 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 Core, Agentic AI

• 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 including 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
• Lead development and benchmarking of multi-turn conversational and tool-using agent workflows with measurable performance and safety metrics
• Implement scalable pipelines for training, fine-tuning, and deploying foundation or domain-specific models
• Collaborate with research and data engineering teams to curate datasets and improve model evaluation methodologies
• Contribute to governance and security efforts for model traceability, lineage documentation, and version control
• Mentor junior AI engineers and advocate for engineering excellence, reproducibility, and responsible experimentation

Manager, Process Manager – Bank Voice Servicing

Senior Associate, Data Scientist – Credit Card Innovation

Commercial Executive Communications Manager

AI Engineer

Manager, HR Strategic Operations

Applied Researcher 4 – AI Foundations, LLM Core, Agentic AI

Principal Associate, HR Strategic Operations

Applied Researcher 5, AI Foundations, LLM Core, Agentic AI

Senior Manager, AI Engineer – Gen AI Platform Services, Agentic AI, Guardrails, Evaluation

AI Engineer 5 – AI Foundations, LLM Core, Agentic AI

Senior Manager, Compliance Advisory – Network Compliance

AI Engineer 5, MLX, Agentic AI, Gen AI platform Services

AI Engineer 5, MLX, Agentic AI, Gen AI platform Services

AI Engineer 4, AI Foundations, LLM Core, Agentic AI

AI Engineer 3, AI Foundations