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

About the role

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real‑time, personalized customer experiences. Our investments in technology infrastructure and world‑class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking.

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand‑in‑hand with partners across the company to advance the state of the art in science and AI engineering, building and deploying proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

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.
• 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 performance — scalability, cost, latency, throughput — of large‑scale production AI systems.
• Contribute to the technical vision and long‑term roadmap of foundational AI systems at Capital One.
• Design, implement and optimize multi‑model orchestration pipelines—integrating LLMs, vector search, and domain‑specific models into unified systems.
• Establish and lead cost‑performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency.
• Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards.
• Mentor Principal and Manager‑level AI engineers, fostering cross‑domain learning and elevating organizational technical maturity.

Requirements

Basic Qualifications:

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

Preferred Qualifications:

• Experience leading development of AI systems with trade‑off decisions around cost, latency, throughput, and accuracy.
• 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g., 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 (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 building agentic AI systems and agentic workflows.
• Passion for staying abreast of the latest AI research and judiciously applying novel techniques in production.
• Excellent communication and presentation skills, with the ability to articulate 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 given requirements (e.g., context length, token inputs, token outputs).

Pay

• McLean, VA: $229,900 – $262,400 (AI Engineer 5)
• Cambridge, MA: $229,900 – $262,400 (AI Engineer 5)
• New York, NY: $250,800 – $286,200 (AI Engineer 5)
• San Francisco, CA: $250,800 – $286,200 (AI Engineer 5)
• San Jose, CA: $250,800 – $286,200 (AI Engineer 5)

This role is also eligible to earn 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 your total well‑being. Eligibility varies based on full‑ or part‑time status, exempt or non‑exempt status, and management level.