AI Engineer 5 (GenAI Platform, Agentic Infrastructure)

Capital One; San Jose (CA); On-site; USD 170,000 - 210,000; Full time

Job summary

Capital One is seeking an AI Engineer 5 to build responsible, scalable AI platforms. You will develop AI software components, including foundation models, LLM inference, and multi-agent workflows, using PyTorch, HuggingFace, and vector databases.

You will optimize performance and drive governance across AI systems. You will mentor engineers and collaborate with cross-functional teams to deliver AI-powered banking experiences.

Qualifications

• Bachelor's or Master's degree with related field and several years of AI/ML experience.
• 6+ years of experience programming in Python or other listed languages.
• Experience leading AI systems with tradeoffs on cost, latency, throughput, and accuracy.

Responsibilities

• Deliver AI-powered products with cross-functional teams.
• Design, develop, test, deploy AI software components (foundation model training, LLM inference, agents, etc.).
• Leverage OSS and SaaS AI tech to build scalable AI infrastructure.
• Improve foundation model optimization for production-scale systems.
• Contribute to technical vision and long-term roadmap of AI systems.
• Architect multi-model orchestration pipelines and cost-performance governance.

Skills

Python

Go

Scala

CUDA

Java

Education

Bachelor's degree in CS / AI / EE / CE

Master's degree in CS / AI / EE / CE

Tools

AWS Ultraclusters

Huggingface

VectorDBs

PyTorch

Job description

AI Engineer 5 (GenAI Platform, Agentic Infrastructure)

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

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good
• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production
• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven
• You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss
• You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown

Basic Qualifications:

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies
• At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java

Preferred Qualifications:

• Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy
• 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, delivering, and supporting complex AI systems

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