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About the Role

At Capital One, we are creating responsible and reliable AI systems to transform banking. We are committed to building world-class applied science and engineering teams to deliver breakthrough product experiences and scalable, high-performance AI infrastructure. You will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses.

Responsibilities

Partner with a cross-functional team of 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, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
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 of large scale production AI systems.
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale.
Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide.
Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture.
Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One’s AI technical leadership.

Requirements

Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 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 8 years of experience developing AI and ML algorithms or technologies.
At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy.
9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud).
Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems.
Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level.
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang.
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
Experience in building agentic AI systems and agentic workflows.
Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production.
Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers.
Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership.
Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance.
Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams.
Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact.
Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs).

Skills

Python
Go
Scala
CUDA
Java
C++
C#
Golang
AWS Ultraclusters
Huggingface
VectorDBs
PyTorch
LLM Inference
Similarity Search
VectorDBs
Guardrails
Memory

Location

Cambridge, MA
McLean, VA
New York, NY
Richmond, VA
San Francisco, CA
San Jose, CA

Work Type

Full-time

Experience Level

Sr. Staff

Education Level

Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields

Salary/Compensations

Cambridge, MA: $314,800 - $359,300
McLean, VA: $314,800 - $359,300
New York, NY: $343,400 - $392,000
Richmond, VA: $286,200 - $326,700
San Francisco, CA: $343,400 - $392,000
San Jose, CA: $343,400 - $392,000

Benefits

Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
Eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).

About the Company

Capital One is creating responsible and reliable AI systems, changing banking for good.
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.
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.

Equal Opportunity

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
Capital One promotes a drug-free workplace.
Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.