AI Engineer 2

About the role

Capital One is building responsible and reliable AI systems to transform banking. The Intelligent Foundations and Experiences (IFX) team partners across the company to advance the state of the art in AI science and engineering, delivering proprietary solutions that serve millions of customers. The team builds and deploys AI models and platforms that enable responsible, scalable, high‑impact AI across the business.

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 associates work and how 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.
• 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 scalability, cost, latency, and throughput of large‑scale production AI systems.
• Contribute to the technical vision and long‑term roadmap of foundational AI systems at Capital One.
• Collaborate on development of safe, high‑quality prompts, evaluation datasets, and automated regression tests for foundation model products.
• Support operational readiness by building deployment pipelines, testing environments, and telemetry for model performance.
• Document learnings and contribute to internal AI engineering standards for reproducibility, monitoring, and ethical deployment.

Basic Qualifications

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 2 years of experience developing AI and ML algorithms or technologies, or a Master’s degree in one of those fields.
• At least 2 years of experience programming with Python, Go, Scala, CUDA, or Java.

Preferred Qualifications

• Experience contributing to development of AI system components with trade‑off decisions around cost, latency, throughput, and accuracy.
• 2+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
• Experience developing, delivering, and supporting AI components.
• 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.
• Knowledge of retrieval‑augmented generation (RAG) and embedding‑based search systems used to ground model outputs in factual context.
• Familiarity with responsible‑AI and safety practices such as model alignment, prompt guardrails, content filtering, and red‑team evaluation.
• Experience with agentic AI observability and performance monitoring frameworks.
• Experience with agentic tools, Model Context Protocol, agent‑to‑agent interoperability, and securing agents.

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

Pay

Full‑time annual salary ranges (by location):

• Cambridge, MA: $135,600 – $154,800
• McLean, VA: $135,600 – $154,800
• New York, NY: $148,000 – $168,900
• San Jose, CA: $148,000 – $168,900

Candidates hired in other locations will receive the pay range associated with that location. This role is also eligible for performance‑based incentive compensation, which may include cash bonuses and/or long‑term incentives.

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support total well‑being. Eligibility varies based on full‑ or part‑time status, exempt or non‑exempt status, and management level.