Capital One

Consultant

• Manage end-to-end One Learn platform logistics for closed session offerings across Learning & Development, including courses, sessions, and enrollments
• Execute designated operational intake tasks within Learning Planner
• Consult with enterprise learning professionals on LMS capabilities, best practices, and optimization opportunities
• Monitor course enrollments, waitlists, and completion trends; generate recurring One Learn reports to guide session capacity and availability decisions
• Provide high-touch support to facilitators on One Learn navigation, platform capabilities, Zoom invites, basic reporting, and roster reconciliation
• Serve as a direct point of contact for learners regarding LMS navigation, course inquiries, and specific offerings
• Liaise between clients and product teams, managing and escalating issues through appropriate channels
• Document processes, team responsibilities, best practices, and training resources
• Identify, propose, and implement One Learn LMS functionality optimizations

Associate Portfolio Logistics Lead, LMS Consultant

Artificial Intelligence

• Partner with data scientists, software engineers, machine-learning engineers, and product managers to deliver AI-powered products
• Use 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 emerging AI developments into customer experiences
• Translate complex research into tangible business goals
• Collaborate with senior researchers on internal technical reports or conference submissions describing novel methods or findings
• Research and evaluate emerging technologies and state-of-the-art methods
• Identify impactful research problems and independently execute long-running research projects

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

Content Marketing Manager

• Co-create innovative solutions to complex problems and influence product strategy
• Craft compelling, accurate, and accessible digital content experiences
• Create content audits, taxonomy and terminology lists, content guidelines and patterns, content governance models, and microcopy
• Develop content for websites, user interfaces, emails, push notifications, and chatbot responses supporting end-to-end user flows
• Lead design projects and direct or delegate work for more junior team members
• Build strong partnerships with cross-functional stakeholders
• Mentor team members and help mature Capital One’s overall product design practice
• Navigate partner and stakeholder needs while ensuring customer-centered and inclusive design
• Apply customer, competitor, and market insights to business challenges
• Use knowledge of technology, data capabilities, and emerging technologies to inform solutions
• Foster collaboration across lines of business and the organization
• Present work across levels and job functions to influence strategic decision-making and direction at senior levels

Content Designer, Manager – Core Card Experiences

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 including AWS Ultraclusters, Hugging Face, vector databases, 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

AI Engineer 5 – Gen AI Platform Services

Researcher

• Partner with data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered banking 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 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
• Choose impactful research problems and autonomously carry out long-running research projects

Applied Researcher 4

General

• Execute high-volume cash transactions, including deposits, withdrawals, and complex negotiable instrument processing
• Maintain security, audit, BSA/AML, and federal regulatory compliance standards
• Educate clients on mobile banking, remote deposit capture, and contactless payments
• Identify client needs and recommend appropriate digital tools or banking solutions
• Greet customers and provide a warm, community-focused experience
• Balance efficient high-volume operations with attentive customer service
• Support surrounding branches within a 50-mile radius as needed
• Occasionally assist other locations in the broader region
• Attend required training sessions
• Help clients achieve personal or business financial goals

Branch Ambassador – Eastern Maryland

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 supporting financial empowerment experiences
• 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 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, implement targeted refactoring, 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

Accounting Manager

• Prepare and review accounting activities, including journal entries, reconciliations, analytics, and support
• Prepare external Securities and Exchange Commission and regulatory reports
• Document and present results to management and senior leadership
• Serve as the main point of contact with business partners on Tax Credit Investment products, primarily LIHTC and Alternative Energy investments
• Assess new or changing business initiatives for impacts on existing processes and VIE/Consolidation reporting
• Respond to requests from Finance, business partners, Controllers Group associates, Operations teams, and auditors
• Present results, findings, risks, and recommendations to leadership and stakeholders
• Collaborate across teams on corporate initiatives
• Contribute to process improvement through project development and knowledge sharing
• Participate in technology and data transformation, process improvement, and business initiatives
• Collaborate with internal and external partners to resolve issues and stay connected on process or product changes

Principal Associate, Commercial Accounting

Solutions Engineer

• Understand desired application capabilities with data, process, owners, and consumers, and explain limitations in non-technical terms
• Build and maintain platform operational aspects, including vulnerability remediation
• Monitor platform support Slack channels and address customer questions and issues
• Keep Google Workspace features and best practices current, implementing updates and improvements
• Improve file storage processes, governance, audit, legal, retention practices, and standards
• Intake, provision, and deploy solutions across lines of business
• Lead platform availability, resilience, and scalability
• Collaborate with Architecture to align platforms with current architecture and configuration
• Encourage innovation, automation, cutting-edge technology, inclusion, teamwork, self-organization, and diversity in legacy processes
• Develop and use best practices to improve platform user experience
• Collaborate with Software Engineers to ensure software works seamlessly on platforms

Integration Engineer - Level 3

• 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 – AI Foundations, LLM Core, Agentic AI

• 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 numeric and textual datasets
• Build AI foundation models through design, training, evaluation, validation, and implementation
• Conduct applied research and advance emerging AI developments into customer experiences
• Translate complex research into tangible business goals
• Collaborate with senior researchers on internal technical reports or conference submissions
• Choose impactful research problems and autonomously carry out long-running projects

Applied Researcher – Level 4

• Design, document, and maintain the enterprise-wide Google Workspace Collaboration Platform
• Design, document, and maintain the enterprise-wide Microsoft M365 Collaboration Platform
• Translate business objectives and risk tolerance into platform configurations, security practices, and data handling policies
• Develop IAM strategy for Google Workspace and/or M365, including MFA, SSO integration, and context-aware access policies
• Architect, implement, and manage a Google Drive content management program to prevent unauthorized sharing of sensitive data
• Maintain lifecycle-based governance processes for third-party applications accessing Workspace data
• Ensure Google Workspace meets regulatory and legal framework requirements through configuration, operation, and auditing
• Apply Google Vault data retention, eDiscovery, and legal holds with Legal, Compliance, and HR
• Identify automation opportunities for repetitive administrative tasks
• Provide technical support, troubleshoot issues, and answer user questions
• Monitor system performance, security, and data integrity; proactively address potential problems
• Implement Google Workspace updates and improvements
• Develop documentation and training materials
• Remediate vulnerabilities and maintain platform operations
• Monitor platform support Slack channels and address customer issues
• Align platforms with current architecture and configuration standards
• Collaborate with software engineers to ensure seamless platform integration
• Work with product owners on application capabilities and testing scenarios
• Improve platform engineering practices and mitigate integration risks
• Design, develop, test, implement, and support technical solutions across Agile teams
• Experiment with new technologies, participate in technology communities, and mentor engineers
• Lead engineering teams and people leaders in platform strategy and Well Managed objectives
• Use scripting languages such as Python and Bash

Integration 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, large language model 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 elevate organizational technical maturity

AI Engineer 5 – Gen AI Platform Services, Agentic Systems

Business Analyst

• Identify business challenges and opportunities for improvement and make strategic or tactical recommendations using analysis
• Perform modeling and analytics to assist new products/models for lines of business within the Commercial Bank
• Support improvements in credit performance by analyzing historical behavior, creating risk models, testing hypotheses, and monitoring results
• Frame problems, develop and test hypotheses, analyze results, develop solutions, assess operational feasibility, lead implementation, and develop monitoring plans
• Work with Model Development, Credit Officers, Underwriters, Relationship Managers, Finance, and other Capital One colleagues
• Evaluate risk-rating and loss-forecasting model prototypes using big data tools and visualization platforms such as Tableau and QuickSight
• Translate complex technical concepts into clear, actionable insights and secure stakeholder buy-in
• Bridge quantitative modelers and senior business leaders as an analytical lead for upcoming model builds

Senior Business Analyst – Commercial Risk Management, Strategy & Analytics

• 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, large language model 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, Huggingface, 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
• Develop safe, high-quality prompts, evaluation datasets, and automated regression tests
• Build deployment pipelines, testing environments, and telemetry for model performance
• Document learnings and contribute to internal AI engineering standards for reproducibility, monitoring, and ethical deployment