Skip to content
Updated How AI-exposed are the skills employers are hiring for? See the data →

From the employer's careers site First seen 14 Nov 2026

AI Engineer 3 (AI Foundations)

Capital One New York, NY Hybrid senior full-time

Salary

$161,800 - $184,600 for AI Engineer 3 per year

Apply on Capital One

Description

At Capital One, we are creating responsible and reliable AI systems, changing banking for good.

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life.

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 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.
  • Lead development and benchmarking of multi-turn conversational and tool-using agent workflows, ensuring measurable performance and safety metrics
  • Implement scalable pipelines for training, fine-tuning and deploying foundation or domain-specific models across multiple environments
  • Collaborate with research and data engineering teams to curate high-quality datasets and improve model evaluation methodologies
  • Contribute to governance and security efforts for model traceability, lineage documentation, and version control of deployed AI assets
  • Mentor junior AI engineers and advocate for engineering excellence, reproducibility, and responsible experimentation

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.
  • 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 are deeply Technical.
  • 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 3 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 1 year of experience developing AI and ML algorithms or technologies
  • At least 3 years of experience programming with Python, Go, Scala, CUDA, or Java

Preferred Qualifications

  • Experience contributing to development of components of AI systems with tradeoff decisions around cost, latency, throughput and accuracy
  • 4+ 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 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
  • Demonstrated ability to evaluate and optimize LLM performance using quantitative metrics (accuracy, coherence, latency, cost)
  • Hands-on experience implementing retrieval-augmented generation (RAG), vector database integrations, and fine-tuning workflows
  • Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies to production AI systems

For more fresh new jobs, check out yubhub.co.

Skills

Nice to have

  • LLM Inference
  • Similarity Search and VectorDBs
  • Guardrails
  • Memory
  • prompt-engineering
  • safety guardrails
  • red-teaming methodologies

Ready to apply?

You apply with the employer directly. Their original posting is here: https://capitalone.wd12.myworkdayjobs.com/en-US/Capital_One/job/New-York-NY/AI-Engineer-3--AI-Foundations-_R1005770-1

Apply on Capital One