Capital One

Program Manager

• Enable continued delivery of the technology organization’s top priorities
• Deliver Cyber capabilities that provide Capital One customers with secure experiences
• Work on capabilities including AI, Data Protection, Cyber Operations and Security Information and Event Management, Cloud Security, and Cyber Governance and Risk
• Potentially lead a team of program managers
• Simplify technically complex topics and drive decisions across product, engineering, design, and data science
• Identify and mitigate technical risks throughout the delivery lifecycle
• Collaborate across functions, organizations, and reporting boundaries
• Own business or technical vision, secure commitments on deliverables, and unblock teams to deliver business impact

Senior Cyber Program 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 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
• 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 foster cross-domain learning

AI Engineer 5 – LLM Gateway, FM Hosting

• 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
• 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 – AI Foundations

Developer Relations

• Serve as a strategic advisor and operating partner to the senior leadership team
• Translate vision into actionable roadmaps and provide a high-context sounding board for executive decision-making
• Create and evolve organizational operating rhythms, including business priorities, routines, and strategic planning processes
• Design and implement scalable tools and processes that enhance organizational effectiveness
• Synthesize disparate data and reporting to bring transparency and rigor to business operations
• Partner with Corporate Finance to synchronize operational roadmaps and financial forecasts
• Serve as the primary interface for organizational planning and resource allocation against fiscal targets
• Connect Product, Tech, Design, and Finance functions around shared objectives
• Lead high-stakes cross-functional special projects independently in a matrixed environment
• Support an Executive Vice President and senior leadership team in improving business efficiency and cross-functional impact

Director, Chief of Staff – Consumer Developer Experience

Product Manager

• Set the strategy, vision, and roadmap for the Support Innovation domain
• Leverage AI and emerging technologies to revolutionize IT support for Capital One's 100,000+ workforce
• Lead a team of product managers and design partners
• Drive modern technology solutions across the enterprise
• Partner with senior engineering, design, and cross-functional leaders
• Translate complex technology into intuitive, delightful experiences for Associates
• Reimagine and innovate product solutions around internal and external customer needs
• Deliver business outcomes through leverage and execution excellence
• Identify and resolve complex problems while mitigating product risks
• Lead cross-functional teams and drive organizational alignment

Senior Director, Product Management – Associate Experience, Support Innovation

• 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 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
• Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation

AI Engineer, Level 4

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 and advance AI developments into 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

Applied Researcher 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 including 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, GenAI Platform Services, Agentic Platform

Technical Program Manager

• Lead programs delivering critical business goals and large-scale products and platforms for Capital One customers
• Expand the TPM discipline by applying industry knowledge and teaching the organization what effective technical program management can achieve
• Contribute to TPM and delivery strategy through scalable operating mechanisms, maturity models, and tooling
• Drive program roadmaps aligned with business objectives, definitions of done, technical solutions, and dependency sequencing
• Lead cross-platform technical investment planning and architectural alignment for long-term platform convergence and reuse
• Serve as an executive-level escalation point for program risks and influence technology leaders on data-driven speed, cost, and resiliency tradeoffs
• Define measurable platform success outcomes, including availability, scalability, cost efficiency, and developer velocity
• Ensure delivery accountability across multiple engineering teams

Director, Technical Program Manager – Core TPM Tower

• Lead programs delivering critical business goals and large-scale products and platforms
• Develop the TPM discipline by teaching the organization what effective technical program management can achieve
• Contribute to TPM and delivery strategy through operating mechanisms, maturity models, and scalable tooling
• Drive program roadmaps aligned with business objectives, definitions of done, technical solutions, and dependency sequencing
• Lead cross-platform technical investment planning and architectural alignment for platform convergence and reuse
• Serve as an executive-level escalation point for program risks
• Influence technology leaders to make data-driven tradeoffs between speed, cost, and resiliency
• Define measurable platform success outcomes, including availability, scalability, cost efficiency, and developer velocity
• Ensure delivery accountability across multiple engineering teams

Director, Technical Program Manager – Resiliency and Reliability Engineering

• 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 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

Risk

• Apply cyber best practices to assess current state, identify gaps, and assess cyber risk, threats, and business impact
• Define, prioritize, and escalate mitigation recommendations
• Perform independent control testing and document results
• Communicate findings to stakeholders
• Project manage assigned engagements to meet defined timelines
• Establish and maintain relationships during testing engagements
• Execute manager-assigned tasks to deliver team objectives
• Collaborate with team members
• Analyze technology systems, including networks, applications, cloud computing, and data
• Inform on cyber risk using reporting metrics
• Analyze data and create charts using Excel/Google Sheets
• Recommend changes to policies, procedures, and control programs to mitigate evolving risks
• Challenge cyber control programs as part of first-line duties and escalate risks when appropriate
• Document and communicate action plans, impediments, risks, and stakeholder engagement

Senior Associate, Technology Controls Testing – Enterprise Services Risk Operations

Data Scientist

• Partner with data scientists, software engineers, and product managers to deliver customer-focused products
• Leverage Python, Conda, AWS, H2O, Spark, and related technologies to analyze large volumes of numeric and textual data
• Build machine learning models through design, training, evaluation, validation, and implementation
• Research and apply emerging technologies, state-of-the-art methods, and applications
• Develop personalized recommendation engines and customer experiences across web and mobile applications
• Conduct research involving Foundation Models, Reinforcement Learning, Causal Inference, Transformer-based architectures, and Recommender Systems
• Translate complex data science work into tangible business goals
• Retrieve, combine, and analyze data from varied sources and structures

Principal Associate, Data Scientist – Recommendation & Personalization Systems

Project Manager

• Drive strategy and execute on high-priority projects for Capital One
• Work with stakeholders across the company to deliver results impacting the company’s bottom line
• Partner with Communications and Business leaders and colleagues across the Enterprise to drive strategic priorities
• Act as an Individual Contributor focused on project management for critical initiatives supporting the Global Payment Network and Technology organization
• Lead project management for critical initiatives in partnership with Communications, Marketing, Business, and Legal teams
• Draft strategic communications updates for key executive forums
• Identify and pilot opportunities to responsibly integrate AI tools into strategic operations workflows
• Improve efficiency in data synthesis, reporting, and team process optimization

Senior Project Manager – Global Enterprise Communications

Communications

• Partner with Line of Business communication leads to co-author and execute comprehensive internal communication strategies for Commercial Bank executives and their organizations
• Write, refine, and produce polished internal content for senior leaders, including organizational announcements, executive talking points, town hall presentations, and strategic team updates
• Elevate client and associate stories across the Commercial Bank
• Manage and modernize internal channels, including intranet sites, ensuring content aligns with executive voice and enterprise Brand standards
• Ensure messaging is precise, accurate, and aligned with the Commercial Communications team’s strategy
• Establish, track, and analyze internal engagement metrics to evaluate communications and recommend strategic adjustments
• Collaborate with Chiefs of Staff, Senior Leadership teams, HR, and horizontal business groups to drive organizational alignment and cultural connection