Capital One seeks a Sr Lead Software Engineer (Full Stack, AI) to develop AI-driven shopping solutions. Requires a bachelor’s degree and at least 6 years of software engineering experience, hands-on with languages and tools such as JavaScript, TypeScript, Python, Go, SQL, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure). Position is remote-eligible and Capital One may sponsor employment authorization.

Capital One is hiring a Senior Distinguished Engineer (remote-eligible) to define technical vision, decompose complex problems, ensure design quality, and mentor engineers. The role expects at least 9 years' experience in software engineering/architecture, deep expertise in cloud technologies and networking (BGP, Wi‑Fi, SD‑WAN, cloud and data center networking), and hands-on coding experience in languages such as Java, Python, Go, JavaScript/TypeScript, or Swift. The position may sponsor work authorization and lists annual salary ranges for remote and McLean, VA locations.

Capital One Staff Engineer role to lead technical vision and hands-on development for AI and automated solutions within Risk Technology (partnering with AML & Sanctions). Responsibilities include full-stack development, cloud and data architecture (event-driven/real-time), system design for performance/scalability/operability, applying ML/AI techniques, SRE and observability practices, mentoring, and driving engineering excellence. Remote-eligible; employer may sponsor work authorization; posted salary ranges vary by location.

Lead technical strategy and roadmap for a personalization platform powering real-time, multi-channel personalized experiences. Responsibilities include designing ML infrastructure and pipelines, building low-latency event-driven systems, MLOps automation, and applying LLM optimization techniques. Requires strong engineering background with at least 10 years designing data-intensive distributed systems and significant experience in ML lifecycle, production deployment, and cloud-native technologies.

Lead, manage and grow multiple product-focused engineering teams; mentor engineers; collaborate with product managers; drive full-stack design, development, testing and deployment in AWS; improve engineering practices, scalability, availability and resilience; and break monoliths into microservices. Technologies called out include Node.js, Java, Go, React, Python, REST/JSON, NoSQL and relational databases, machine learning and big data.