Staff AI Engineer - Enterprise Analysis Platform (Remote Eligible)

Capital One · Remote (Remote US)

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About the role

Staff AI Engineer - Enterprise Analysis Platform (Remote Eligible)

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 currently working on building a new AI native platform to empower our broader business community to execute AI assisted analysis across our many lines of business. We are building an AI native, at-scale (15,000+ users at destination), enterprise platform intertwining deterministic code with non-deterministic reasoning systems as well as both frontier and home grown AI models, to transform how our company works in the data analysis space.

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.

Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams

Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads

Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design

Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds

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

Continued in Capital One’s original posting ↗.

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