AI Engineer (GenAI, Agentic Infrastructure)

Requirements:

• We require a bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, plus at least 6 years of experience developing AI and ML algorithms or technologies; or a masters degree in one of those fields plus at least 4 years of equivalent experience.
• We require at least 6 years of programming experience with Python, Go, Scala, CUDA, or Java.
• We prefer candidates with experience leading AI system development where tradeoffs among cost, latency, throughput, and accuracy must be balanced.
• We prefer 7 years of experience delivering scalable, responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud environments.
• We prefer experience designing, building, delivering, and supporting complex AI systems.
• We prefer experience developing AI and ML technologies such as LLM inference, similarity search, vector databases, guardrails, or memory using Python, C++, C#, Java, CUDA, or Golang.
• We prefer experience applying advanced optimization techniques to improve training and inference efficiency, hardware utilization, latency, throughput, and cost.
• We prefer experience building agentic AI systems and agentic workflows.
• We prefer strong communication and presentation skills, with the ability to explain complex AI concepts clearly to peers.
• We prefer experience architecting and integrating heterogeneous AI systems, including rule-based, retrieval-augmented, and generative components, into production pipelines.
• We prefer experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes.
• We prefer demonstrated ability to balance model performance and operating cost through dynamic inference strategies and model compression.
• We prefer experience right-sizing models, instance counts, and hardware types based on requirements such as context length, token inputs, and token outputs.

Responsibilities:

• We partner with cross-functional 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.
• We design, develop, test, deploy, and support AI software components, including foundation model training, large language model inference, agents, multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• We leverage a broad stack of open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, vector databases, PyTorch, and related tools.
• We invent and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput for large-scale production AI systems.
• We contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
• We design, implement, and optimize multi-model orchestration pipelines that integrate LLMs, vector search, and domain-specific models into unified systems.
• We establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency.
• We lead design councils or design review boards to ensure technical consistency and adherence to AI engineering standards.
• We mentor Principal- and Manager-level AI engineers, encouraging cross-domain learning and strengthening organizational technical maturity.

Technologies:

• Agentic AI
• AI
• AWS
• Azure
• C#
• Cloud
• CUDA
• Golang
• Hardware
• Support
• Java
• LLM
• Model Training
• PyTorch
• Python
• Scala
• DevOps
• Machine Learning

More

Capital One is building responsible and reliable AI systems to help transform banking for good. Our Intelligent Foundations and Experiences (IFX) team sits at the center of that vision, partnering across the company to advance science and AI engineering and to build proprietary solutions that support millions of customers. We provide the infrastructure and platforms that enable teams to enhance their products with scalable, high-impact AI. This role is eligible for salary ranges that vary by location, performance-based incentive compensation, and a comprehensive benefits package that supports overall well-being. Capital One also notes that it will consider sponsoring a new qualified applicant for employment authorization for this position.

last updated 43 week of 2026