AI Engineer 3 (AI Foundations)

Capital One is building AI systems that help associates work more effectively and improve how customers interact with the bank. In this role, you will join the Intelligent Foundations and Experiences (IFX) team to design, deploy, and evolve foundation-model and agent capabilities, with a focus on responsible and scalable delivery of production AI.

You will work across a cross-functional group that includes engineers, research scientists, technical program managers, and product managers, contributing to the technical vision and long-term roadmap for foundational AI systems at Capital One. The work spans model training and inference through evaluation, experimentation, governance, and observability, supporting AI experiences used across the company and at customer scale.

What you’ll do

• Partner with cross-functional teams to deliver AI-powered products that impact associate workflows and customer experiences.
• Design, develop, test, deploy, and support AI software components covering foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Use a broad stack of Open Source and SaaS AI technologies including AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
• Introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput for large-scale production AI systems.
• Lead development and benchmarking of multi-turn conversational and tool-using agent workflows, including 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 strengthen model evaluation methodologies.
• Contribute to governance and security work such as model traceability, lineage documentation, and version control of deployed AI assets.
• Mentor junior AI engineers and promote engineering excellence, reproducibility, and responsible experimentation.

Minimum qualifications

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 3 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in the same fields plus at least 1 year of experience developing AI and ML algorithms or technologies.
• At least 3 years of experience programming with Python, Go, Scala, CUDA, or Java.

Preferred qualifications

• Experience making tradeoffs for AI systems components around cost, latency, throughput, and accuracy.
• 4 years of experience deploying scalable and responsible AI solutions on cloud platforms (AWS, Google Cloud, Azure, or equivalent private cloud).
• Experience developing, delivering, and supporting AI services.
• Experience building AI and ML algorithms or technologies (including LLM inference, similarity search and VectorDBs, guardrails, and memory) using Python, C++, C#, Java, CUDA, or Golang.
• Experience applying state-of-the-art techniques to optimize training and inference software for improved hardware utilization, latency, throughput, and cost.
• Experience building agentic AI systems and agentic workflows.
• Demonstrated ability to evaluate and optimize LLM performance using quantitative metrics such as accuracy, coherence, latency, and cost.
• Hands-on experience implementing retrieval-augmented generation (RAG), vector database integrations, and fine-tuning workflows.
• Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies to production AI systems.

Tools and technologies you may use

• AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
• AWS, Google Cloud, Azure
• Python, Go, Scala, CUDA, Java, C++, C#, Golang
• Retrieval-augmented generation (RAG)

Compensation and location

• Location: McLean, VA (onsite)
• Salary range: USD 161,800 - 184,600 per year

Benefits

• Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

Note on entities: Capital One Financial is made up of several different entities. Positions posted in Canada are for Capital One Canada, in the United Kingdom for Capital One Europe, and in the Philippines for Capital One Philippines Service Corp. (COPSSC).