AI Engineer 5 (Gen AI Platform Services)

Capital One; San Jose (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Capital One is pioneering responsible AI systems and scalable AI infrastructure. The IFX team collaborates with engineers, researchers, and product managers to deliver AI‑powered products that transform how associates work and how customers interact with Capital One.

You will design and deploy AI software components, including foundation models, LLM inference, and multi‑model orchestration, while advancing a long‑term roadmap for foundational AI systems across the company.

Responsibilities

• Partner with a cross‑functional team of engineers, research scientists, technical program managers, and product managers to deliver AI‑powered products that change how our associates work and how our customers interact with Capital One.
• 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, etc.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
• Invent and introduce state‑of‑the‑art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
• Design, implement and optimize multi‑model orchestration pipelines - integrating LLMs, vector search, and domain‑specific models into unified systems
• Establish and lead cost‑performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency
• Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards
• Mentor Principal and Manager‑level AI engineers, fostering cross‑domain learning and elevating organizational technical maturity

Job description

Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real‑time, personalized customer experiences. Our investments in technology infrastructure and world‑class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world‑class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high‑performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand‑in‑hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

What You’ll Do:

• Partner with a cross‑functional team of engineers, research scientists, technical program managers, and product managers to deliver AI‑powered products that change how our associates work and how our customers interact with Capital One.
• 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, etc.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
• Invent and introduce state‑of‑the‑art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
• Design, implement and optimize multi‑model orchestration pipelines - integrating LLMs, vector search, and domain‑specific models into unified systems
• Establish and lead cost‑performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency
• Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards
• Mentor Principal and Manager‑level AI engineers, fostering cross‑domain learning and elevating organizational technical maturity