Capital One

Manager

• Optimize inbound channels such as EASE, Email, and Site through models and frameworks
• Support the Modeling function and evaluate potential model improvements
• Develop comprehensive model roadmaps
• Advise Lines of Business on potential operational impacts
• Converge business, credit, and modeling results
• Develop business strategies driving growth, profitability, and competitive success
• Manage and develop 1–2 analysts, including coaching and mentoring
• Develop and implement product and pricing strategies for lending products
• Lead product-level modeling and analytics
• Lead direct-to-consumer marketing efforts and strategic intent for retail-channel products
• Build targeted insights for new customer experiences, technology, and go-to-market strategies
• Improve credit performance using consumer credit trends, historical behavior, risk models, and rigorous monitoring
• Manage and sequence business intent delivery, build business requirements, and execute product strategy
• Oversee multiple projects and programs concurrently
• Collaborate with IT, Sales, Operations, Finance, and other Capital One teams
• Drive critical decisions, hold business partners accountable, and deliver short- and long-term results

Business Manager – Enterprise Arbitration, Enterprise Consumer Product

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 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

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

Full-stack Engineer

• Lead a portfolio of diverse technology projects and a team of developers using distributed microservices and full-stack systems
• Create solutions that meet regulatory needs
• Stay current with technology trends, experiment with and learn new technologies, and participate in technology communities
• Mentor members of the engineering community
• Collaborate with digital product managers to deliver robust cloud-based solutions supporting millions of Americans
• Use programming languages, open-source relational and NoSQL databases, Docker, Kubernetes, and AWS tools and services
• Provide technical leadership across Agile teams and set standards for design, development, and operational excellence
• Partner with architects to define service boundaries, integration patterns, and reusable frameworks
• Identify improvement opportunities, perform targeted refactoring, reduce technical debt, and enhance system performance
• Influence long-term technology strategy by evaluating emerging tools and practices in a 'you build it, you own it' environment

Full-stack Engineer, Level 4

Machine Learning Engineer

• Design, build, and deliver ML models and components solving real-world business problems
• Collaborate with Product and Data Science teams
• Build and scale multi-tenant platforms for large-scale ML model training and serving
• Inform ML infrastructure decisions using knowledge of modeling techniques, data, feature selection, training, tuning, dimensionality, bias/variance, and validation
• Write and test application code, develop and validate ML models, and automate tests and deployment
• Collaborate in cross-functional Agile teams to create and enhance big data and ML applications
• Retrain, maintain, and monitor production models
• Build or leverage cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
• Construct optimized data pipelines feeding ML models
• Apply CI/CD best practices, test automation, and monitoring for ML model and application deployment
• Manage code to reduce vulnerabilities and govern models from a risk perspective
• Apply Responsible and Explainable AI best practices
• Use programming languages such as Python, Scala, or Java

Machine Learning Engineer, Level 5

• Lead a portfolio of diverse technology projects and a team of developers with experience in distributed microservices and full-stack systems
• Create solutions that meet 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 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 improve system performance
• Influence long-term technology strategy through evaluation of emerging tools and practices in a 'you build it, you own it' environment

Solutions Engineer

• Work with product owners to understand desired application capabilities and testing scenarios
• Continuously improve software engineering practices
• Design, develop, test, implement, and support technical solutions across a full stack of development tools and technologies
• Lead the craftsmanship, availability, resilience, and scalability of solutions
• Stay current with technology trends, experiment with and learn new technologies, participate in technology communities, and mentor engineers
• Encourage innovation, cutting-edge technology adoption, inclusion, teamwork, self-organization, and diversity
• Design, develop, and implement robust integration solutions connecting enterprise applications, including Salesforce CRM and Google Cloud services
• Serve as a senior technical authority for integration design, automation, and system interoperability across platforms and business domains
• Lead development of reusable integration frameworks, libraries, and patterns
• Partner with enterprise architects to define integration architecture standards and evaluate emerging connectivity technologies

Integration Engineer

Product Manager

• Lead the Collections and Recoveries Web and Mobile experiences
• Own the Collections and Recoveries customer experience via the mobile app and web presence
• Envision the future destination of Collections and Recoveries experiences and bring those visions to life
• Work with design, marketing, operations, compliance, business analysts, and data scientists
• Lead product managers overseeing two web teams and two mobile teams
• Manage complex customer experience initiatives impacting millions of customers and driving significant business value
• Balance short-term urgent needs with experimentation for the future
• Keep customer promises in a provably well-managed way
• Lead cross-functional teams to solve customer problems and drive organizational alignment

Senior Manager, Product Management – Customer Resiliency, Web and Mobile App Experience Lead

• Lead a portfolio of diverse technology projects and a team of developers using distributed microservices and full-stack systems
• Create solutions that 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 programming languages including Java, Scala, Python, Go, Node.js, JavaScript, and TypeScript
• Work with open-source relational and NoSQL databases, Docker, Kubernetes, and AWS tools and services
• Provide technical leadership across Agile teams and establish standards for design, development, and operational excellence
• Partner with architects to define service boundaries, integration patterns, and reusable frameworks
• Identify improvement opportunities, perform targeted refactoring, reduce technical debt, and enhance system performance
• Influence long-term technology strategy by evaluating emerging tools and practices in a 'you build it, you own it' environment

Full-stack Engineer – IC

Project Manager

• Lead high-impact strategic initiatives transforming Finance operations
• Orchestrate a portfolio of high-priority, complex initiatives across the Finance organization
• Provide executive visibility through concise, decision-oriented progress updates
• Own strategic communications across executives, stakeholders, and delivery teams
• Identify cross-program connections, overlaps, competing priorities, and opportunities
• Manage risks, dependencies, capacity constraints, and mitigation plans
• Establish decision-management mechanisms and ensure decisions translate into action
• Translate strategic priorities into executable plans, outcomes, workstreams, milestones, and success criteria
• Anticipate upcoming needs, decisions, risks, and organizational impacts
• Identify, evaluate, prioritize, and implement AI opportunities that simplify work, automate activities, improve insights, or enhance operations
• Provide reporting and analytics on AI portfolio adoption, resource demand, and project health using self-service tools
• Introduce tools, AI capabilities, automation, and operating practices to improve program delivery

Manager, Project Manager – AI Transformation & Delivery

Data Scientist

• Partner with cross-functional data scientists, software engineers, and product managers to deliver customer-focused products
• Leverage 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 technical work into tangible business goals
• Research and evaluate emerging technologies and state-of-the-art methods
• Experiment, innovate, and create next-generation experiences powered by emerging machine learning technologies
• Deliver machine learning solutions supporting the enterprise data lifecycle

Principal Data Scientist – AI Foundations, Specialist Models

• 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

AI Engineer – Level 3

• Lead, manage, and grow multiple teams of product-focused software engineers
• Mentor and guide engineers' professional and technical development
• Partner with product managers to understand application capabilities and testing scenarios
• Continuously improve software engineering practices
• Design, develop, test, implement, and support full-stack technical solutions across Agile teams
• Lead the craftsmanship, availability, resilience, and scalability of solutions
• Stay current with technology trends, experiment with and learn new technologies, and participate in technology communities
• Encourage innovation, cutting-edge technology adoption, inclusion, teamwork, self-organization, and diversity
• Improve the velocity of multiple teams
• Lead deployment of new and existing applications into AWS environments
• Guide migration of monolithic applications to microservice architectures and build new microservices
• Shape long-term technical strategy and architecture standards for enterprise platforms
• Partner with senior engineering and business leaders to align product roadmaps with scalable technology capabilities
• Drive talent strategy, succession planning, skill development, and equitable opportunity across engineering teams

Director, Full-Stack Engineer

Consultant

• Translate strategic business objectives into impactful learning and knowledge solutions and learner-centered experiences
• Partner with Intent Owners, operations leaders, and business stakeholders to co-create the annual strategic learning and knowledge agenda
• Ensure seamless integration and execution across business and learning initiatives
• Apply iteration, experimentation, and feedback to improve solutions
• Manage project scope, timelines, and budget; identify, mitigate, or escalate risks
• Conduct learning needs analysis and manage the full life cycle of learning requests
• Balance demand with capacity using data-driven decision frameworks
• Identify workflow breakdowns and embed learning solutions within operational processes
• Collaborate with business partners in a matrixed environment to align solutions with performance drivers
• Build and maintain stakeholder relationships as a trusted advisor
• Diagnose business problems using consulting frameworks and root cause analysis
• Determine whether learning, process, tooling, or organizational interventions are required
• Use data and insights to drive decisions and continuous improvement
• Define success metrics aligned to business KPIs
• Assess intake and determine which learning and knowledge solutions can drive business intent
• Communicate clearly and influence senior and technical audiences
• Collaborate on learner communications and external storytelling, sharing insights and outcomes of learning and knowledge solutions
• Proactively enhance business outcomes through learning and knowledge solutions

Manager – Strategic Learning, Knowledge Consultant

• 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
• Set technical direction for enterprise-wide AI architecture, tooling, observability, and deployment standards
• Own the design and integration of model routing, caching, and orchestration systems for hybrid and multi-model workloads
• Champion responsible AI principles, including transparency, reproducibility, and fairness-by-design
• Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds

Staff AI Engineer

Risk

• Execute major components of audits covering critical technology functions, cloud-based infrastructure, cybersecurity, risk management, applications, and third-party management
• Assist in leading components of 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
• Assess financial, legal, reputational, and other risks affecting the business and critical technology functions
• Establish and maintain client relationships during engagements
• Communicate audit results to management through written reports and oral presentations
• Prepare clear, organized, and complete documentation supporting work performed
• Plan and prioritize work across multiple tasks and deliver quality results
• Coordinate with others and take on additional work
• Communicate audit information, issues, and progress to teammates, clients, and the auditor-in-charge
• Perform engagement administration, including hours and budget tracking
• Provide on-the-job coaching and direct supervision to less experienced associates