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

Capital One’s Intelligent Foundations and Experiences (IFX) team is seeking an AI Engineer 5 to build and deploy responsible, scalable AI systems. The role focuses on foundation model training and LLM inference, agentic workflows, evaluation and guardrails, observability, optimization, and multi-model orchestration for production-grade platform services.

Role Context

Within IFX, you will partner with engineering, research science, technical program management, and product teams to deliver AI-powered products that improve how associates work and how customers engage with Capital One. Work spans the design, development, testing, deployment, and ongoing support of core AI software components.

Key Responsibilities

• Collaborate with cross-functional teams of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for associates and customers.
• Design, develop, test, deploy, and support AI 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 set of Open Source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
• Develop and introduce foundation model optimization techniques that improve scalability, cost, latency, and throughput for large-scale production AI systems.
• Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
• Design, implement, and optimize multi-model orchestration pipelines that integrate LLMs, vector search, and domain-specific models into unified systems.
• Establish and lead cost-performance governance reviews across AI systems, including tracking GPU utilization, model throughput, and inference cost efficiency.
• Lead team design councils or design review boards to maintain technical consistency and compliance with AI engineering standards.
• Mentor Principal and Manager-level AI engineers by supporting cross-domain learning and raising 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 developing AI and ML algorithms or technologies.
• At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.

Preferred Qualifications

• Experience leading development of 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 environments.
• Experience designing, developing, delivering, and supporting complex AI systems.
• Experience building AI and ML algorithms or technologies such as LLM inference, similarity search and vector databases, guardrails, and memory using Python, C++, C#, Java, CUDA, or Golang.
• Experience applying state-of-the-art training and inference optimization techniques to improve hardware utilization, latency, throughput, and cost.
• Experience building agentic AI systems and agentic workflows.
• Strong interest in current AI research and systems, with the ability to apply novel techniques in production judiciously.
• Excellent communication and presentation skills, including the ability to explain 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 ethical AI deployment standards, including explainability, fairness, and human-in-the-loop review processes.
• Proven 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 and token inputs/outputs.

Technologies

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

Team Overview

The Intelligent Foundations and Experiences (IFX) team is central to bringing Capital One’s AI vision to life. The team works with partners across the company to advance the state of the art in science and AI engineering, and to build and deploy proprietary solutions that deliver value to millions of customers.

IFX AI models and platforms enable teams across Capital One to enhance products with the transformative power of AI in responsible and scalable ways, targeting 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 fields.