C

Capital One

Issues credit cards and runs a consumer bank

AI Engineer 3 - AI Foundations

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 3 years of experience developing AI and machine learning algorithms or technologies, or a master's degree in those fields plus at least 1 year of such experience.
  • At least 3 years of experience programming with Python, Go, Scala, CUDA, or Java.

Responsibilities

  • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for associates and customers.
  • 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.
  • Use open-source and software-as-a-service AI technologies such as AWS Ultraclusters, Hugging Face, vector databases, and PyTorch.
  • Develop foundation model optimization techniques to improve the scalability, cost, latency, and throughput of large-scale production AI systems.
  • Contribute to the technical vision and long-term roadmap of foundational AI systems.
  • Lead development and benchmarking of multi-turn conversational and tool-using agent workflows, ensuring measurable performance and safety metrics.
  • Implement scalable pipelines for training, fine-tuning, and deploying foundation or domain-specific models across multiple environments.
  • Collaborate with research and data engineering teams to curate high-quality datasets and improve model evaluation methodologies.
  • Contribute to governance and security efforts for model traceability, lineage documentation, and version control of deployed AI assets.
  • Mentor junior AI engineers and advocate for engineering excellence, reproducibility, and responsible experimentation.

Desired Qualifications

  • Experience contributing to development of AI system components, making tradeoff decisions involving cost, latency, throughput, and accuracy.
  • Four years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or an equivalent private cloud.
  • Experience developing, delivering, and supporting AI services.
  • Experience developing AI and machine learning algorithms or technologies, such as large language model inference, similarity search and vector databases, guardrails, and memory, using Python, C++, C#, Java, CUDA, or Golang.
  • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
  • Experience building agentic AI systems and workflows.
  • Demonstrated ability to evaluate and optimize large language model performance using quantitative metrics such as accuracy, coherence, latency, and cost.
  • Hands-on experience implementing retrieval-augmented generation, vector database integrations, and fine-tuning workflows.
  • Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies to production AI systems.

About the Company

Capital One

Issues credit cards and runs a consumer bank

Capital One runs a consumer and commercial bank that issues credit cards, takes deposits, and finances cars and businesses. Its Venture travel cards and Quicksilver cash-back cards let customers earn rewards on everyday spending, while its online banking tools manage payments and savings. Customers use checking and savings accounts through an app, branches, and cash machines, and commercial clients use treasury tools to manage company cash. The bank earns interest on loans and fees from banking and card transactions, with customer deposits helping fund its lending operations. Capital One was founded in 1994 and has its headquarters in McLean, Virginia.

Company size
10,001+
Company stage
IPO
Headquarters
McLean, VA
Founded
1994

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