Capital One

Risk

• Maintain the definitive inventory of monitored employees within Broker-Dealer and Swap Dealer business lines
• Track internal transfers, role changes, and status updates for regulatory compliance coverage
• Manage end-to-end onboarding and offboarding workflows for monitored associates
• Coordinate with Licensing & Registration, Swap Dealer/Broker Dealer Advisory, Technology, and Mobility teams
• Validate provisioning across compliance surveillance tools, databases, and communication channels
• Design and execute daily, weekly, and monthly data reconciliation processes
• Identify, investigate, and remediate roster gaps and anomalies
• Serve as the primary contact for population scoping, access issues, and roster discrepancies
• Streamline workflows, automate manual reconciliation tasks, and refine procedures
• Escalate operational gaps, technical setup failures, and potential compliance risks to leadership

Senior Associate, Risk Specialist – eComm Surveillance Population Management

Full-stack Engineer

• 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 Java, Scala, Python, Go, Node.js, JavaScript, TypeScript, open-source RDBMS and NoSQL databases, Docker, Kubernetes, and AWS tools and services
• Provide technical leadership across multiple teams and shape system architecture and long-term technology direction
• Drive end-to-end design and implementation of large-scale, distributed, or cloud-native systems with high reliability and performance requirements
• Partner with architects and product leaders to define platform roadmaps and shared-services strategy

Full-stack Engineer 5 – Shopping

Software Engineer

• Partner with software engineers, designers, and product managers to deliver high-performing features for 100M+ customers
• Provide technical leadership for mobile architecture and design patterns
• Mentor engineers through feedback, code reviews, and platform-specific best practices
• Identify and clear technical obstacles
• Grow and provide subject matter expertise in performance, accessibility, and architecture
• Contribute to mobile architecture decisions, API design reviews, and reusable component development
• Lead the design and development of client Backend-for-Frontends and Server-Driven UI architectures
• Lead engineering practices and define best practices for feature flags and staged rollouts
• Champion adoption of agentic AI tools and mentor engineers in AI-native development practices
• Apply advanced mobile ecosystem expertise to make high-leverage technical contributions
• Establish high standards for coding, testing, performance, accessibility, and user experience

Mobile Engineer 4 – Android

Data Scientist

• Partner with cross-functional teams of data scientists, machine learning engineers, and product managers to deliver Generative AI solutions
• Use Python, LangChain, AWS, Workflows, and Vector Databases to build Multi-Agent systems and advanced RAG pipelines over numeric and textual data
• Build Generative AI models and pipelines through context engineering, fine-tuning, evaluation, validation, and deployment
• Research and evaluate emerging technologies and state-of-the-art methods, technologies, and applications
• Translate complex technical work into tangible business goals
• Develop and apply data science solutions using open-source tools and cloud computing platforms

Principal Associate, Data Scientist – Applied AI

• Partner with cross-functional teams of data scientists, machine learning engineers, and product managers to deliver Generative AI solutions
• Use Python, PyTorch, LangChain, AWS, Spark, and vector databases to build multi-agent systems and advanced RAG pipelines
• Build Generative AI models and pipelines through context engineering, fine-tuning, evaluation, validation, and deployment
• Research and evaluate emerging technologies and state-of-the-art methods
• Translate complex data science work into tangible business goals
• Develop data science solutions using open-source tools and cloud computing platforms
• Operate across large volumes of numeric and textual data to support data-driven decision-making

Senior Associate, Data Scientist – Applied AI

Product Manager

• Lead the Spend Controls Team within the Employee Spend pillar of Business Cards & Payments
• Lead product managers and analysts driving the pre-authorization spend controls roadmap
• Own card management and virtual card number (VCN) strategy
• Lead the technical migration of the spend-limit decisioning platform onto modern infrastructure
• Partner with engineering, design, risk, and Enterprise platform teams to deliver spend controls
• Ship controls that influence customer behavior and support real-time transaction decisioning
• Share a roadmap and prioritization forum with the Expense Management team
• Demonstrate proficiency in Capital One's Product Framework: Human Centered, Business Focused, Technology Driven, Integrated Problem Solving, and Transformational Leadership

Senior Manager, Product Manager – Spend Controls Lead, Business Cards & Payments

Data Analyst

• Drive current and future strategy through analytical skills
• Build and use models to test and validate data
• Work with vast amounts of data in new and evolving environments
• Leverage analytics to improve customer experience
• Lead, mentor, and develop junior analysts
• Participate in the full life cycle of projects
• Collaborate across business units
• Mine data to identify crucial organizational information
• Implement process, data, and reporting improvements
• Work with large and complex databases containing millions to billions of records
• Improve operational efficiency and effectiveness
• Conduct analysis to evaluate processes and tests
• Extract and analyze data to gauge product offerings
• Consult on the design and implementation of production and data storage systems
• Develop and implement strategic tests for products, initiatives, and marketing materials

Manager, Data Analysis

• Lead a portfolio of diverse technology projects and a team of developers experienced in 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 millions of Americans
• Use Java, Scala, Python, Go, Node.js, JavaScript, TypeScript, open-source relational and NoSQL databases, Docker, Kubernetes, and AWS tools and services
• Provide technical leadership across multiple teams and shape system architecture and long-term technology direction
• Drive end-to-end design and implementation of large-scale, distributed, or cloud-native systems with high reliability and performance requirements
• Partner with architects and product leaders to define platform roadmaps and shared-services strategy
• Build high-throughput, real-time streaming pipelines and services evaluating credit-card transactions for fraud
• Develop machine-learning feature engineering, continuous experimentation, and agentic tooling for advanced data analysis

Full-stack Engineer 5, Senior Manager, IC

Data Engineer

• Lead, manage, and grow multiple teams of product-focused software and data engineers
• Incubate emerging technology and open-source products across platforms
• Modernize existing technology stacks and data platforms
• Collaborate with internal teams on automation and machine learning opportunities
• Partner with architects, product owners, data professionals, and engineers to implement new applications
• Work across Agile teams to design, develop, test, implement, and support technical solutions
• Deploy applications into AWS environments and provide operational support
• Conduct design and code reviews for standards compliance
• Communicate technical concepts and data outcomes to internal and external stakeholders
• Oversee data platform and pipeline design and health, including scalability, resilience, and operational efficiency
• Mentor engineers and elevate team capabilities through hands-on technical contribution
• Lead transformative data initiatives end to end, making architectural decisions and evaluating platforms such as Snowflake and Databricks

Senior Director, Data Engineer

• Execute test procedures for critical technology functions, cloud-based infrastructure, cybersecurity, risk management, applications, and third-party management
• Perform business-activity risk assessments and relevant testing based on associated risks and processes
• Communicate issues, risks, and recommendations to all levels of management
• Operate independently and complete work on schedule and to high-quality standards
• Prepare clear, organized, and complete audit documentation
• Develop and maintain effective relationships with business partners and the extended Audit group
• Leverage data and analytical tools during audit planning and fieldwork
• Follow up on agreed audit actions to ensure management commitments are delivered on time
• Seek learning opportunities to enhance role-related skills and competencies

Senior Associate, Tech Risk & Analysis – Technology Audit

• Develop and manage account and transaction data products used by data consumers across the Bank and broader Enterprise
• Manage a large and diverse ecosystem of stakeholders and data consumers
• Support use cases spanning fraud and AML modeling, real-time customer-facing experiences, and other enterprise needs
• Lead a team of 10+ product managers with specialized expertise in data modeling and governance
• Bring clarity and simplicity to complex topics and problem solving
• Influence cross-functional partners and manage stakeholders
• Continuously refine and simplify operating models in pursuit of shared outcomes
• Reimagine and innovate product solutions around internal and external customer needs
• Deliver 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 to solve customer problems and drive organizational alignment

Senior Director, Data Product Management

Program Manager

• Lead programs that deliver critical business goals and build large-scale products and platforms
• Establish TPM operating mechanisms, maturity models, and tooling across portfolios
• Drive program roadmaps aligned with business objectives, technical solutions, and dependency sequencing
• Lead cross-platform technical investment planning and architectural alignment toward 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
• Expand the TPM discipline by teaching the organization what effective TPM practices can achieve

Director, Technical Program Management

• Execute major components of audits covering critical technology functions, cloud-based infrastructure, emerging technology, cybersecurity, risk management, application, and third-party management
• Lead small to medium-sized audits
• Perform risk assessments of business units and technology operations
• Design and execute audit procedures to verify control effectiveness
• Identify and define issues, review and analyze evidence, and document client processes and procedures
• Understand financial, legal, reputational, and other risks affecting the business and critical technology functions
• Establish and maintain client relations during engagements
• Communicate audit results to management through written reports and oral presentations
• Identify client expectations and support the client experience
• Prepare clear, organized, and complete documentation
• Plan work activities and manage multiple priorities and tasks
• Coordinate with others and proactively take on additional work
• Tailor communication to the audience and communicate issues and audit progress
• Perform engagement administration, including hours and budget tracking
• Provide on-the-job coaching and direct supervision to less experienced associates

Audit Manager – Tech Risk & Analysis

Cloud Engineer

• Lead a portfolio of diverse technology projects and a team of developers experienced in distributed microservices and full-stack systems
• Build and enhance internal tools, platforms, and AI-powered workflows, including Claude Code integrations and skills marketplaces
• Improve engineering productivity, code quality, and developer experience through developer tooling
• Collaborate with digital product managers to deliver robust, scalable AWS cloud solutions
• Use programming languages including Java, Scala, Python, Go, Node.js, JavaScript, and TypeScript
• Work with open-source RDBMS and NoSQL databases, Docker, Kubernetes, and modern AWS infrastructure
• Provide technical leadership across Agile teams and promote system design, software development, operational excellence, and ownership culture
• Partner with enterprise architects to define service boundaries, integration patterns, reusable frameworks, and long-term technology strategy
• Identify technical debt, implement targeted refactoring, and optimize system performance
• Track emerging technology trends, experiment with new technologies, participate in tech communities, and mentor engineering peers

Full-stack Engineer 4, Cloud Native, Microservices, AWS

• 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
• Translate complex data science work into tangible business goals
• Develop real-time customer behavioral prediction and valuation forecasting solutions for the US Card customer management business
• Collaborate with cross-functional teams including business, engineering, analytics, data science/quants, and product teams
• Develop talent within the team and beyond