Capital One

Data Engineer

• Collaborate across Agile teams to design, develop, test, implement, and support technical solutions
• Influence developers, data analysts, and data scientists working with machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Use Python and Spark, 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 professionals
• 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
• Build and deploy AI-powered proprietary risk-management solutions with the GRC team and company partners

Data Engineer 4 – Manager, IC

Full-stack Engineer

• Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices and full-stack systems
• Create solutions that help 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 programming languages, open-source relational and NoSQL databases, container orchestration services, 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
• Partner with architects and product leaders to define platform roadmaps and shared-services strategy

Full-stack Engineer 5, Senior Manager – IC

• Lead a portfolio of diverse technology projects and a team of developers building distributed microservices and full-stack systems for regulatory needs
• Stay current with technology trends, experiment with and learn new technologies, participate in technology communities, mentor engineers, and occasionally code or evaluate code
• Collaborate with digital product managers to deliver robust cloud-based solutions supporting financial empowerment
• Lead teams using Java, Scala, Python, Go, Node.js, JavaScript, TypeScript, RDBMS and NoSQL databases, Docker, Kubernetes, and AWS services
• Lead multiple Agile engineering teams or programs and ensure delivery of large-scale, cross-functional initiatives
• Partner with product, architecture, and platform leaders to define multi-year technology roadmaps and investment priorities
• Develop and manage Lead Engineers and engineering leads, building succession plans and scaling leadership capability
• Align engineering execution with enterprise goals and influence portfolio-level decisions and trade-offs
• Drive end-to-end design and implementation of large-scale distributed and cloud-native systems with high reliability and performance requirements

Senior Manager, Full-stack Engineer – People Leader

• Lead a portfolio of diverse technology projects and a team of developers building distributed microservices and full-stack systems for regulatory needs
• Stay current with technology trends, experiment with and learn new technologies, participate in internal and external technology communities, and mentor engineering team members
• 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 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, implement 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 4 – Manager, IC

• Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices and full-stack systems
• Build and deploy proprietary AI-powered risk management solutions with the GRC team and partners across the company
• 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 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 – Senior Manager, IC

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 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
• Build responsible and reliable AI systems and scalable, high-performance AI infrastructure for Capital One's banking products

AI Engineer 5 – FM Hosting, LLM Inference

Product Manager

• Collaborate with cross-functional partners to understand customer, live chat agent, and business needs
• Use data-driven and test-and-learn approaches to identify valuable intersections among customer, agent, and business needs
• Co-develop plans to grow chat servicing among US Card customers and onboard additional lines of business
• Prioritize and sequence the roadmap to scale chat servicing and expand the platform beyond US Card
• Partner with technology counterparts to provide technical requirements and enable day-to-day delivery
• Lead cross-functional teams through complex dependencies and ambiguity
• Influence partners across job families to advance the chat servicing platform and deliver superior message-based servicing experiences
• Prepare the Chat Platform for tenant onboarding and manage requirements and timelines across lines of business

Manager, Product Management – Chat Core Services

• 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

• Champion initiatives within the Chat Servicing team to extend Chat beyond Card and reach new customer audiences
• Prepare the Chat Platform for tenant onboarding
• Interface with senior management across lines of business to manage requirements and timelines
• Collaborate with cross-functional partners to understand customer, live chat agent, and business needs
• Use data-driven and test-and-learn approaches to identify valuable intersections across needs
• Co-develop plans to grow chat servicing among US Card customers and onboard additional lines of business
• Prioritize and sequence the roadmap to scale chat servicing and expand beyond US Card
• Partner with technology counterparts on technical requirements, design, and day-to-day delivery
• Lead cross-functional teams through complex dependencies and ambiguity
• Influence partners across job families to deliver superior message-based servicing experiences

Senior Manager, Product Management – Chat Servicing Expansion

General Counsel

• Manage, draft, and negotiate procurement transactions supporting multiple lines of business and functional groups
• Identify legal issues and risks in procurement and outsourcing contracts
• Work with legal stakeholders to draft appropriate terms and conditions
• Advise on internal guidelines and procedures
• Build and maintain relationships with Enterprise Supplier Management and legal stakeholders
• Manage repeatable, controlled processes for transactional work
• Manage and coordinate outside counsel, including service delivery and costs, when necessary
• Create reports and discuss trends and metrics with senior Legal and ESM leaders
• Create and provide training on key issues and processes as needed
• Act as backup Legal representative in procurement risk gate meetings
• Determine whether transactions are in scope for Legal engagement
• Delegate and manage assignments for backup attorneys as needed

Manager, Counsel – Enterprise Supplier Management

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 related 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 next-generation customer experiences
• Translate complex research into tangible business goals
• Lead research threads bridging prototype model development and deployment with ML engineering partners
• Ensure scientific insights translate into production impact

Applied Researcher 5 – AI Foundations, LLM Core, Agentic AI

• Partner with cross-functional 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
• 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 – AI Foundations, LLM Core, Agentic AI

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 engineering community members
• Encourage innovation, cutting-edge technology implementation, inclusion, outside-the-box thinking, teamwork, self-organization, and diversity
• Design, develop, and implement robust integration solutions connecting enterprise applications, including Salesforce CRM and Google Cloud services (GCP)
• Lead complex, enterprise-scale integrations across multiple systems, data sources, and platforms
• Serve as technical integration lead for major initiatives, partnering with software, data, and infrastructure teams to ensure interoperability and performance
• Define integration standards, patterns, and best practices across teams

Integration Engineer, Level 4

• Manage Google Workspace, including Gmail, Calendar, Drive, and Meet
• Provide technical support, troubleshoot issues, and answer user questions
• Monitor system performance, security, and data integrity
• Implement Google Workspace updates and improvements
• Develop documentation and training materials for users
• Build and maintain platform operational capabilities, including vulnerability remediation
• Monitor platform support Slack channels and address customer issues
• Lead platform availability, resilience, and scalability
• Collaborate with the Architecture team on platform architecture and configuration
• Encourage automation, innovation, and adoption of emerging technologies
• Develop and apply best practices to improve user experience
• Use scripting languages such as Python and Bash
• Work with Docker, ECS, Ansible, Terraform, and AWS tools and services
• Collaborate with Software Engineers to ensure software works seamlessly on the platforms

Integration Engineer, Level 3

Researcher

• 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 AI developments into customer experiences
• Translate complex research into tangible business goals
• Lead cross-functional research threads bridging prototype development and deployment with ML engineering partners
• Choose impactful research problems and independently pursue long-running research projects
• Design and lead small-scale research initiatives, guiding junior researchers or engineers through experimental design and evaluation