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Capital One is a financial services and fintech company offering credit cards, auto loans, banking, and savings products. Its work combines financial expertise with technology and digital tools to improve how customers manage money. The company’s careers focus includes building customer-oriented solutions within a diverse and inclusive workforce.
Staff AI Engineer, Capital One — United States Remote
Lead the design of responsible, scalable AI systems for Capital One’s banking products. Shape foundation models, agentic workflows, optimization strategies, and enterprise AI architecture.
Description
- Collaborate with engineering, research, program, and product teams to deliver AI-powered products
- Build and operate AI software spanning foundation-model training, LLM inference, agents, similarity search, guardrails, evaluation, governance, experimentation, and observability
- Apply open-source and SaaS technologies including AWS Ultraclusters, Hugging Face, vector databases, and PyTorch
- Develop advanced techniques for optimizing foundation models
- Increase the scalability, efficiency, throughput, and responsiveness of production AI systems
- Help define the technical vision and long-term roadmap for foundational AI platforms
- Establish enterprise AI architecture direction and standardize tooling, observability, and deployment practices
- Lead the design and integration of model routing, caching, and orchestration for hybrid and multi-model workloads
- Promote responsible AI through transparency, reproducibility, and fairness-by-design
- Expand internal expertise through mentoring, education, architecture councils, and AI guilds
Requirements
- Bachelor’s degree in computer science, AI, electrical engineering, computer engineering, or a related field plus 8+ years developing AI or ML algorithms and technologies; or a relevant master’s degree plus 6+ years of experience
- 8+ years programming in Python, Go, Scala, CUDA, or Java
- Experience designing AI systems while balancing cost, latency, throughput, and accuracy
- Experience deploying scalable, responsible AI solutions on AWS, Google Cloud, Azure, or an equivalent private cloud
- Experience architecting, building, integrating, delivering, and supporting complex AI systems
- Experience leading and mentoring multiple engineering teams and influencing cross-functional stakeholders through the VP level
- Experience developing AI and ML algorithms or technologies with Python, C++, C#, Java, CUDA, or Golang
- Experience optimizing training and inference software for hardware utilization, latency, throughput, and cost
- Experience building agentic AI systems and workflows
- Experience applying AI research and novel techniques in production environments
- Strong communication and presentation skills for explaining complex AI concepts
- Proven ability to define and operationalize enterprise AI architecture standards, including data-pipeline governance, observability, and evaluation frameworks
- Experience leading federated or multi-cloud AI strategies
- Experience influencing processes that promote research into production
- Experience defining north-star metrics for AI systems
- Experience right-sizing models, instance counts, and hardware types
- Capital One may consider employment-authorization sponsorship for a new qualified applicant
Benefits
- Performance-based incentive compensation, potentially including cash bonuses and long-term incentives
- Comprehensive health, financial, and other benefits designed to support overall well-being
- Employment-authorization sponsorship may be considered for a new qualified applicant
- Reasonable accommodations are available for applicants who need them
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