Capital One

Operations

• Lead day-to-day activities of a high-visibility, multi-function, multi-team operation
• Create a vision and strategy enabling well-managed, customer-focused execution
• Build relationships across stakeholders and partners and prioritize high-leverage organizational needs
• Translate insights and data into stories that drive individual, team, and business goals
• Lead Customer Escalations/Complaints, Specialty Operations, Fraud Operations, Coaching, and Training processes
• Lead 3 Senior Associate people leaders overseeing approximately 40 specialty production associates
• Coordinate core functions of approximately 200 vendor call center and funding agents
• Create a roadmap covering process streamlining, associate engagement/development, escalation framework, customer experience mapping, training, and documentation
• Monitor Fraud queue backlog and complex cases; guide resolution or escalation
• Develop escalation interaction models and invest in reporting and tools
• Maintain effective Refi Fraud/ID Theft controls
• Gather vendor escalation trends and identify training or policy gaps
• Use Sentinel for real-time intervention and data
• Identify process or product gaps using complaint data and partner across functions to close them
• Monitor intraday call center and funding performance to deploy Flex production associates
• Establish coaching frameworks and quality calibrations
• Develop coaching skills and frameworks for empathetic, human-centered customer experiences
• Audit, update, and improve onboarding, upskilling, and refresher training content
• Implement closed-loop feedback mechanisms for training improvements
• Build relationships with UMs and frontline associates while maintaining a positive culture
• Make strategic pivots and key business decisions autonomously
• Guide UMs in performance management and associate development
• Identify gaps in process, reporting, tools, and customer experience and partner with leadership/product teams
• Serve as proxy for the Senior Department Manager as needed

Auto Refinance Department Operations Manager

Product Manager

• Lead the Data Standardization and Governance strategy for data from the Utah Processing Center and Capital One’s in-house Perso Bureau
• Own outcomes related to improvements in the production system, including reconciliation, self-healing controls, and managed improvements for in-house card production
• Apply improvements from in-house production to third-party suppliers to improve SLAs, cost, and production quality
• Partner with Data Analysts, Correspondence Product teams, and Platform tenants to understand evolving production-data needs
• Develop strategies to connect the data product across the Capital One ecosystem where appropriate
• Understand customers through empathy and design thinking
• Build a customer-backed product roadmap that drives business value
• Lead cross-functional teams, solve customer problems, and drive organizational alignment

Manager, Product Management – Correspondence Production Data

Full-stack Engineer

• Lead a portfolio of diverse technology projects and a team of developers with distributed microservices and full-stack systems experience
• Create solutions that help meet the company's regulatory needs
• Stay current with technology trends, experiment with and learn new technologies, and participate in internal and external technology communities
• Mentor members of the engineering community
• Collaborate with digital product managers to deliver robust cloud-based solutions
• Use programming languages, open-source relational and NoSQL databases, container orchestration services, and AWS tools and services
• Provide technical leadership and direction across Agile teams
• Set standards for design, development, and operational excellence
• Partner with architects to define service boundaries, integration patterns, and reusable frameworks
• Identify improvement opportunities through targeted refactoring and technical-debt reduction
• Enhance system performance
• Influence long-term technology strategy through evaluation of emerging tools and practices in a “you build it, you own it” environment

Full-stack Engineer, Manager

• Lead a portfolio of diverse technology projects and a team of developers building distributed microservices and full-stack systems
• Create solutions that meet regulatory needs for Capital One
• Stay current with technology trends, experiment with and learn new technologies, and participate in internal and external technology communities
• Mentor members of the engineering community
• Collaborate with digital product managers to deliver robust cloud-based solutions supporting financial empowerment
• Use Java, Scala, Python, Go, Node.js, JavaScript, TypeScript, open-source RDBMS and NoSQL databases, Docker, Kubernetes, and AWS tools and services
• Provide technical leadership and direction across Agile teams
• Set standards for design, development, and operational excellence
• Partner with architects to define service boundaries, integration patterns, and reusable frameworks
• Identify areas for improvement through refactoring and efforts to reduce technical debt and enhance system performance
• Influence long-term technology strategy through evaluation of emerging tools and practices in a “you build it, you own it” environment

Full Stack Engineer 4, Bank Tech

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 at Capital One
• Define and steer the technical AI architecture vision, integrating applied research breakthroughs into reliable, scalable production ecosystems
• Lead the establishment of AI performance, safety, and transparency standards for company-wide model development and deployment
• Drive multi-year platform initiatives unifying data, compute, and model lifecycle management under an enterprise AI architecture
• Mentor senior technical leaders across research, data, and engineering disciplines

Senior Staff AI Engineer

Security Engineer

• Lead, mentor, and develop associates by setting expectations, providing feedback, and supporting career progression
• Serve as a cybersecurity subject matter expert and advise on risk reduction through configuration of cybersecurity tools and platforms
• Support development, modification, and use of capability, risk, and threat classification frameworks and standardization methodologies
• Support continuous improvement programs, including risk and issue identification, corrective action implementation, and results validation
• Identify and operationalize linkages among threats, risks, controls, capabilities, tooling, and data analytics to support prioritization and resource allocation
• Lead solutioning and manage activities for large-scale enterprise risk reduction efforts
• Communicate operational, compliance, process, control, and tooling gaps and remediation options to leadership and other audiences
• Lead cross-domain cybersecurity risk assessments and capability reviews aligned with enterprise control standards, business objectives, and regulator expectations
• Coordinate risk reduction initiatives across cyber programs and drive consistency in control design, testing, and reporting

Senior Manager, Cyber Security

• Lead the ongoing advancement of cybersecurity capabilities and services
• Partner with stakeholders and conduct assessments to determine capability effectiveness and risk management practices using tools and frameworks such as NIST CSF
• Leverage cybersecurity data from multiple sources to produce insights, risk indicators, and program metrics
• Provide expertise during control and risk assessments
• Document, assign ownership of, and track issues and remediation plans to closure
• Drive adoption of automation and tooling for control monitoring, issue management, and risk reporting workflows
• Synthesize and present cyber-risk insights for senior management forums
• Highlight trends, systemic issues, and risk-reduction opportunities
• Mentor and guide associates, fostering consistent application of cyber-risk management methodologies and professional growth

Manager, Cyber Security, Cyber Fraud Intelligence

Data Scientist

• Partner with cross-functional data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products
• Leverage PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and other technologies to analyze numeric and textual data
• Apply Natural Language Processing and Large Language Models to customer-facing applications and features
• Adapt and fine-tune language models
• Build machine learning and NLP models through design, training, evaluation, and validation
• Partner with engineering teams to operationalize models in scalable and resilient production systems serving 80+ million customers
• Translate complex technical work into tangible business goals
• Research and evaluate emerging technologies and state-of-the-art methods
• Challenge conventional thinking and improve the status quo with stakeholders
• Support talent development for the team and beyond
• Influence cross-functional teams in AI/ML innovations
• Communicate findings clearly to non-technical audiences

Manager, Data Science – People Tech

Artificial Intelligence

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

Applied Researcher 5 – AI Foundations, LLM, Optimization, Finetuning

• Lead, mentor, and develop associates by setting expectations, providing feedback, and supporting career progression
• Serve as a cybersecurity subject matter expert and advise on risk reduction through configuration of cybersecurity tools and platforms
• Support development, modification, and use of capability, risk, and threat classification frameworks and standardization methodologies
• Support continuous improvement programs, including risk and issue identification, corrective action implementation, and results validation
• Identify and operationalize linkages among threats and risks, controls, capabilities, tooling, and data analytics to support prioritization and resource allocation
• Lead solutioning and manage activities for large-scale enterprise risk reduction efforts
• Communicate operational, compliance, process, control, and tooling gaps and remediation options to multiple audiences, including leadership
• Lead cross-domain cybersecurity risk assessments and capability reviews aligned with enterprise controls, business objectives, and regulator expectations
• Coordinate risk reduction initiatives across multiple cyber programs and drive consistency in control design, testing, and reporting practices

Senior Lead, Cyber Security – GPN

• Reimagine the status quo and identify value creation opportunities through product management
• Drive innovative and sustainable customer experiences through technology
• Develop strategy for the Enterprise Feature Platform
• Deliver innovative solutions and define measures of business impact
• Enable scalable, high-performance foundation models and accelerate the Machine Learning Development Lifecycle
• Replace fragmented data and infrastructure sprawl with a unified, intelligent platform
• Develop agentic workflows and simplify the platform experience
• Enable internal developers and data scientists to build AI solutions faster
• Lead cross-functional teams, solve customer problems, and drive organizational alignment
• Apply human-centered, business-focused, technology-driven, integrated problem-solving, and transformational-leadership product practices

Manager, Product Management – AI/ML, Enterprise Feature Platform

Product Operations

• Establish and maintain Commercial Product’s OKR methodology, reporting routines, and tracking cadences
• Equip product teams with frameworks and templates to align local deliverables with strategic metrics
• Manage Commercial’s Jira platform operations, reporting, and team-level enablement
• Drive adoption of standardized Jira workflow taxonomy
• Execute organization-wide associate engagement programs, capability-building routines, and talent development tracking
• Drive operational discipline across product teams through standardized Jira workflows, OKR tracking cadences, and talent enablement routines
• Create and maintain operational artifacts for MBRs, QBRs, and executive stakeholder engagement
• Partner with cross-functional stakeholders and leadership to provide strategic and tactical thought partnership
• Put structure in place to manage complex bodies of work

Principal Associate, Project Manager – Product Operations, Execution & Talent Enablement

• Lead a portfolio of diverse technology projects and a team of developers building distributed microservices and full-stack systems
• Share knowledge of technology trends, experiment with and learn new technologies, participate in internal and external technology communities, and mentor engineers
• Collaborate with digital product managers to deliver robust cloud-based solutions supporting millions of Americans' financial empowerment
• Use programming languages including Java, Scala, Python, Go, Node.js, JavaScript, and TypeScript
• Work with open-source relational and NoSQL databases
• Use container orchestration services including Docker and Kubernetes and AWS tools and services
• Provide technical leadership across multiple teams and shape system architecture and long-term technology direction
• Lead end-to-end design and implementation of large-scale, distributed, and cloud-native systems with high reliability and performance requirements
• Partner with architects and product leaders to define platform roadmaps and shared-services strategy
• Transform risk management through Risk Management Tech and AML and Compliance Tech products supporting regulatory requirements and BSA/AML compliance

Full-stack Engineer 5, Python, Typescript, React, AWS

Program Manager

• Lead programs that deliver critical business goals and build large-scale products and platforms
• Drive architectural alignment, technical strategy, and execution of organizational objectives and key results
• Improve scalability and system resilience across the Global Payment Network engineering lifecycle
• Own complex technical dependencies and cross-functional engineering roadmaps
• Deliver robust global financial infrastructure
• Proactively identify and mitigate technical risks throughout delivery
• Grow and develop a team of Technical Program Managers and build the TPM practice
• Simplify technical complexity and drive informed decisions across product, engineering, design, and data science
• Drive execution, follow-through, accountability, and results
• Collaborate across functions, organizations, and reporting boundaries to deliver outcomes

Director, Technical Program Management

Data Engineer

• Collaborate across Agile teams to design, develop, test, implement, and support technical solutions
• Influence developers, data analysts, and data scientists with expertise in machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Use Python and Spark, open-source relational and NoSQL databases, and cloud data warehousing platforms including Databricks and Snowflake
• Stay current with data trends, experiment with new technologies, participate in technology communities, and mentor data community members
• Collaborate with product managers and software engineers to deliver cloud-first data solutions
• Independently design, build, and deliver cloud data solutions and applications
• Architect and enforce data engineering design patterns for code quality, maintainability, and reusability
• Communicate technical concepts and data outcomes to internal and external stakeholders
• Design and build scalable, resilient, and operationally efficient data pipelines and platforms
• Implement data security standards including encryption and fine-grained access control