AI Engineer 4 (AI Foundations, LLM Core and Agentic AI)

Capital One National Association; New York (NY); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One National Association is seeking an AI Engineer 4 in New York to build responsible AI systems, including foundation model training, inference, and agentic workflows. You will work with engineers, researchers, PMs, and product leaders to deliver scalable AI experiences for customers and associates.

You will optimize performance, latency, and cost using a broad stack of AI tools, while ensuring security, governance, and observability across deployments.

Qualifications

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 4 years of AI/ML experience, or a Master's with at least 2 years of experience.
• At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java.

Responsibilities

• Partner with a cross-functional team of engineers, researchers, program managers, and product managers to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents, and workflows.
• Leverage a broad stack of Open Source and SaaS AI technologies (AWS Ultraclusters, HuggingFace, VectorDBs, PyTorch).
• Invent and introduce foundation model optimization techniques for performance, latency, and cost.
• Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.
• Own end-to-end architecture for complex AI systems with maintainability and observability.
• Define and maintain SLOs for AI reliability including latency and model performance drift.
• Collaborate with infrastructure to optimize GPU/TPU usage and accelerate model inference.
• Lead cross-functional reviews for new AI deployments ensuring security and governance.
• Mentor senior associates on scalable design and research-to-production translation.

Skills

Python

Go

Scala

CUDA

Java

LLM Inference

VectorDBs

Guardrails

GPU/TPU optimization

Machine Learning

Distributed Systems

Education

Bachelor's degree

Master's degree

Tools

AWS Ultraclusters

HuggingFace

VectorDBs

PyTorch

Guardrails

Model Evaluation

Observability

Job description

AI Engineer 4 (AI Foundations, LLM Core and Agentic AI)

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.

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.
• Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment
• Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift
• Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines
• Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met
• Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation

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 4 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 2 years of experience developing AI and ML algorithms or technologies
• At least 4 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
• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, developing, delivering, and supporting AI services
• 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
• Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale
• Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules
• Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position

Minimum and maximum full‑time annual salaries

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Cambridge, MA: $197,300 - $225,100 for AI Engineer 4McLean, VA: $197,300 - $225,100 for AI Engineer 4New York, NY: $215,200 - $245,600 for AI Engineer 4San Francisco, CA: $215,200 - $245,600 for AI Engineer 4San Jose, CA: $215,200 - $245,600 for AI Engineer 4

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

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.