Staff AI Engineer
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Job Description
Staff AI Engineer building responsible, scalable AI infrastructure and products. Optimizing foundation models, agentic workflows, and enterprise AI architecture for Capital One banking.
Responsibilities:
- 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
Requirements:
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies; or a Master's degree in those fields plus at least 6 years of experience
- At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java
- Experience designing AI systems with tradeoff decisions around cost, latency, throughput, and accuracy
- Experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud
- Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems
- Experience leading and mentoring multiple engineering teams and influencing cross-functional stakeholders up to the VP level
- Experience developing AI and ML algorithms or technologies using Python, C++, C#, Java, CUDA, or Golang
- Experience developing and applying state-of-the-art techniques for optimizing training and inference software
- Experience building agentic AI systems and agentic workflows
- Experience defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability, and evaluation frameworks
- Experience leading federated or multi-cloud AI strategies
- Experience influencing research-to-production promotion processes
- Experience defining north-star metrics for AI systems
- Experience right-sizing models, instance counts, and hardware types
- Capital One will consider sponsoring a new qualified applicant for employment authorization
Benefits:
- Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
- Comprehensive, competitive, and inclusive health, financial and other benefits supporting total well-being
- Reasonable accommodations for applicants who require them
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