Jobs at Capital One

Lead design, development, deployment, and optimization of large-scale AI/ML systems (training, inference, orchestration, observability). Collaborate cross-functionally to build responsible, scalable generative AI and agentic platforms, improve performance and cost, and shape long-term ML systems roadmap.

Lead the development of AI software components for Capital One, including model training, inference, and system optimization. Collaborate with cross-functional teams to deliver groundbreaking AI solutions, ensuring quality and scalability while mentoring junior team members.

The role involves developing AI foundation models, collaborating with cross-functional teams, and conducting applied research to enhance customer experiences using advanced AI techniques.

The role involves leading AI research projects, building AI foundation models, collaborating with engineering teams, and mentoring applied scientists to enhance customer interactions through AI.

As a Lead AI Engineer at Capital One, you will design and develop AI systems, collaborate with cross-functional teams, and optimize AI solutions for performance and scalability.

As a Distinguished AI Engineer, you will design and develop AI software, partner with cross-functional teams, and create optimized AI systems to enhance customer interaction and improve banking services.

This role involves partnering with teams to develop AI-powered technology, advancing applied research in AI, and delivering impactful models. Candidates will work on foundational models and leverage new technologies to optimize customer interactions with banking services.

The role involves partnering with cross-functional teams to design, develop, and deploy AI software solutions, focusing on large language models and AI optimization techniques.

Lead a team delivering cloud-based back-end financial systems, architect distributed microservices, collaborate with product managers, mentor engineers, and build scalable data and reporting solutions using modern languages, containers, and cloud services.

Partner with teams to deliver AI-powered products, build foundation models, and conduct applied research to enhance customer experiences.

As a Lead Platform Engineer, you will develop solutions on Workday for HR, improve data quality, and lead integration teams. Collaborate with stakeholders to ensure cohesive system configurations and optimize business processes using Agile methodologies.

Lead and grow multiple software, data, and platform engineering teams to build scalable, cloud-native data infrastructure, analytics engines, and ML-enabled pipelines. Partner with product and data science, elevate engineering practices, and deploy resilient AWS-based solutions using modern data technologies and CI/CD.

Lead and grow a full-stack engineering team delivering cloud-native, microservices-based risk management solutions. Collaborate with product managers, mentor engineers, oversee architecture and delivery, and occasionally contribute code. Drive adoption of modern cloud, container, and AI/ML technologies to build scalable, compliant systems.

Lead and manage a team delivering full-stack, cloud-based microservices solutions for risk management. Collaborate with product managers, mentor engineers, evaluate and occasionally write code, and drive adoption of modern tech (cloud, containers, databases, AI tooling) to meet regulatory and business needs.

Lead design, build, deploy, and support scalable, responsible AI systems (foundation model training, LLM inference, similarity search, guardrails, observability). Collaborate with cross-functional teams, optimize model performance and cost, and shape technical vision and roadmap for foundational AI platform services.

Drive applied research to build and deploy AI foundation models end-to-end. Partner with cross-functional teams to design, train, evaluate, validate, and implement large-scale models using open-source tools and cloud infrastructure. Mentor scientists, translate research into business goals, and publish/represent Capital One in the research community.

Lead a team of Product Managers building financial forecasting platforms for the CFO organization. Define product strategy, governance, and roadmaps; partner with Finance, Data, and Technology; embed with stakeholders to translate needs into prioritized outcomes; mentor product teams and represent portfolio strategy to senior leadership.

Lead an Agile team to design, build, deploy, and maintain production-scale ML models and pipelines. Drive ML architecture, model training, CI/CD, monitoring, and cloud/Kubernetes-based deployments while ensuring responsible, explainable, and well-governed ML solutions.

Lead a cross-organizational program to transition engineering to an AI-driven, self-optimizing ecosystem with robust telemetry and evaluation. Orchestrate strategy and execution, mitigate technical risk, build and grow a TPM practice, align product/engineering/design/data science, and deliver measurable business impact.

Lead technology projects and a team to design and deliver cloud-based, full-stack and back-end microservices solutions. Collaborate with product managers, mentor engineers, adopt new technologies, and ensure scalable experiences using containers, orchestration, databases, and cloud services.