AI Engineer 4

Capital One’s Intelligent Foundations and Experiences (IFX) team is building responsible, scalable AI systems that support foundation model capabilities across the organization. In this role, you will design, develop, deploy, and support AI software components, with an emphasis on performance across cost, latency, throughput, and reliability.

You will collaborate with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that shape how associates work and how customers engage with Capital One. The work spans end-to-end architecture for training, LLM inference, agents and multi-agent workflows, evaluation, governance, and observability.

What you’ll do

• Work with a cross-functional team to deliver AI-powered products for internal associates and external customers.
• 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 such as AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
• Introduce state-of-the-art foundation model optimization techniques to 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.
• Own end-to-end architecture for complex AI systems, focusing on maintainability, observability, and ethical alignment.
• Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift.
• Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
• Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met.
• Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation.

Skills and experience

• Hold a Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in a related field plus at least 2 years of experience.
• Have at least 4 years of experience programming with Python, Go, Scala, CUDA, or Java.

Technologies

• Open Source AI technologies, AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
• Python, Go, Scala, CUDA, Java
• GPU, TPU
• Foundation model training, large language model inference, agents, multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, observability

Team context

• The Intelligent Foundations and Experiences (IFX) team brings Capital One’s AI vision to life.
• The team works with partners across the company to advance AI science and engineering and to build and deploy proprietary solutions central to the business.
• AI models and platforms from IFX help teams enhance products with responsible and scalable AI for high-leverage impact to millions of customers.

Preferred qualifications

• Experience leading development AI systems with tradeoff decisions around cost, latency, throughput, and accuracy.
• 6+ 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 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 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.
• Experience designing distributed systems for model training, evaluation, and online inference at petabyte scale.
• Experience defining AI model governance processes, including producibility, lineage tracking, and automated retention schedules.
• Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.

Salary and incentives

• Cambridge, MA: $197,300 - $225,100 per year (AI Engineer 4).
• McLean, VA: $197,300 - $225,100 per year (AI Engineer 4).
• New York, NY: $215,200 - $245,600 per year (AI Engineer 4).
• San Jose, CA: $215,200 - $245,600 per year (AI Engineer 4).
• This role may be eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI).

Other information

• No agencies please.
• Capital One is an equal opportunity employer committed to non-discrimination in compliance with applicable federal, state, and local laws (EOE, including disability/vet).
• Capital One promotes a drug-free workplace.
• Capital One will consider qualified applicants with a criminal history in a manner consistent with applicable laws regarding criminal background inquiries.
• Accommodation requests for employment opportunities can be directed to Capital One Recruiting at 1-800-304-9102 or [email protected].
• For technical support or questions about the recruiting process, contact [email protected].
• Capital One does not endorse or guarantee third-party products, services, or information available through this site.