AI Engineer 4

Capital One • San Jose, CA

1d

About The Position

Capital One’s Intelligent Foundations and Experiences (IFX) team builds proprietary AI models and platforms that help teams across the company deliver responsible, scalable AI capabilities to customers and associates. The AI Engineer 4 partners with engineers, research scientists, technical program managers, and product managers to develop AI-powered products and foundational AI systems. The role encompasses AI software development from design and testing through deployment and support, including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.

The engineer uses open-source and SaaS AI technologies, develops optimization techniques for production AI systems, and contributes to the technical vision and long-term roadmap for foundational AI at Capital One. The position owns architecture for complex AI systems, establishes reliability objectives, works with infrastructure teams to optimize accelerator utilization and inference, leads technical reviews for deployments, and mentors Principal and Senior Associates. The work emphasizes maintainability, observability, ethical alignment, security, data governance, compliance, and production performance.

Requirements

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field and at least 4 years of experience developing AI and ML algorithms or technologies; or a master’s degree in one of those fields and at least 2 years of such experience.
• At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java.

Nice To Haves

• Experience leading AI systems development and making tradeoff decisions involving cost, latency, throughput, and accuracy.
• 6 or more years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
• Experience designing, developing, delivering, and supporting AI services.
• Experience developing AI and ML algorithms or technologies such as LLM inference, similarity search and VectorDBs, guardrails, and memory using Python, C++, C#, Java, CUDA, or Golang.
• Experience developing and applying state-of-the-art training and inference optimization techniques to improve hardware utilization, latency, throughput, and cost.
• Experience building agentic AI systems and workflows.
• Interest in following current AI research and systems and applying novel techniques judiciously in production.
• Proficiency designing distributed systems for model training, evaluation, and online inference at petabyte scale.
• Experience defining AI model governance processes, including producibility, lineage tracking, and automated retraining schedules.
• Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.

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, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Use open-source and SaaS AI technologies, including AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch.
• Develop foundation model optimization techniques that improve scalability, cost, latency, and throughput in large-scale production AI systems.
• Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
• Own the end-to-end architecture of complex AI systems, ensuring maintainability, observability, and ethical alignment.
• Define and maintain service-level objectives for AI reliability, including latency, uptime, and model performance drift.
• Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
• Lead cross-functional technical reviews for AI system deployments, ensuring security, data governance, and compliance standards are met.
• Mentor Principal and Senior Associates on scalable design, performance tuning, and translating research into production.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior