AI Engineer 5 (MLX, Agentic AI, Gen AI platform Services)

The AI Engineer 5 role within Capital One’s Intelligent Foundations and Experiences (IFX) team focuses on designing, training, and deploying responsible, scalable AI systems that support foundation model capabilities, agentic workflows, and GenAI platform services.

Role Overview

You will work with a cross-functional group of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that improve how associates work and how customers interact with Capital One. The work spans foundation model training, LLM inference, agentic and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability. You will also help drive optimization and multi-model orchestration across production systems.

Key Responsibilities

• Partner with cross-functional teams to deliver AI-powered products that change associate workflows and customer experiences.
• 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.
• Use a broad stack of Open Source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
• Introduce state-of-the-art foundation model optimization techniques to improve performance across scalability, cost, latency, and throughput for large-scale production AI.
• Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
• Design, implement, and optimize multi-model orchestration pipelines by integrating LLMs, vector search, and domain-specific models into unified systems.
• Establish and lead cost-performance governance reviews, tracking GPU utilization, model throughput, and inference cost efficiency.
• Lead team design councils or design review boards to support technical consistency and compliance with AI engineering standards.
• Mentor Principal and Manager-level AI engineers to promote cross-domain learning and elevate organizational technical maturity.

Required Qualifications

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies; or a Master’s degree in a related field plus at least 4 years of experience.
• At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.

Preferred Qualifications

• Experience leading development AI systems with tradeoff decisions across cost, latency, throughput, and accuracy.
• 7 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
• Experience designing, developing, delivering, and supporting complex AI systems.
• Experience developing AI and ML algorithms or technologies (including LLM inference, similarity search and VectorDBs, guardrails, and memory) using Python, C++, C#, Java, CUDA, or Golang.
• Experience applying state-of-the-art techniques to optimize training and inference software for improved hardware utilization, latency, throughput, and cost.
• Experience building agentic AI systems and agentic workflows.
• Passion for staying current with AI research and applying novel techniques thoughtfully in production.
• Excellent communication and presentation skills for articulating complex AI concepts to peers.
• Experience architecting and integrating heterogeneous AI systems, including rule-based, retrieval-augmented, and generative components, into unified production pipelines.
• Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes.
• Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression.
• Experience right-sizing models, instance counts, and hardware types based on requirements such as context length, token inputs, and token outputs.

Technologies

• AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
• Python, Go, Scala, CUDA, Java
• AWS, Google Cloud, Azure
• C++, C#, Golang

Team Description

The Intelligent Foundations and Experiences (IFX) team brings Capital One’s AI vision to life. The team works closely with partners across the company to advance the state of the art in science and AI engineering, and it builds and deploys proprietary solutions central to business outcomes and value for millions of customers. AI models and platforms enable teams across Capital One to enhance products with responsible, scalable AI for high-leverage impact.

Location and Compensation

• Location: McLean, VA (onsite)
• Salary: USD 229,900 - 262,400 per year

Education

Bachelor’s degree in Computer Science/AI/Electrical Engineering/Computer Engineering (or related). Acceptable alternatives include a Master’s degree in a related field based on the required years of experience.