AI Engineer 4 (Gen AI Platform Services) - Mc Lean

Requirements:

• Bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field and at least 4 years of experience developing AI/ML algorithms or technologies; or a relevant masters degree and at least 2 years of that experience
• At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java
• Experience leading AI systems development and making trade-offs among cost, latency, throughput, and accuracy
• Preferred: 6 years of experience deploying scalable, responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or an equivalent private cloud
• Experience designing, delivering, and supporting AI services and developing AI/ML technologies such as LLM inference, similarity search, vector databases, guardrails, or memory
• Experience optimizing AI training and inference software to improve hardware utilization, latency, throughput, and cost
• Experience building agentic AI systems and workflows
• Ability to keep current with AI research and apply suitable new techniques in production
• Proficiency in distributed systems for model training, evaluation, and online inference at petabyte scale
• Experience defining AI model governance processes, including producibility, lineage tracking, and automated retraining schedules
• Demonstrated ability to influence architecture across multiple AI product lines or platforms
• Strong engineering and mathematics foundations, technical curiosity, adaptability, resilience, and a commitment to responsible, high-quality work

Responsibilities:

• Partner with engineers, research scientists, technical program managers, and product managers to build AI products for associates and customers
• Design, develop, test, deploy, and support AI software, including foundation-model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, evaluation, experimentation, governance, and observability
• Work with open-source and SaaS AI technologies, including AWS Ultraclusters, Hugging Face, vector databases, and PyTorch
• Develop foundation-model optimization techniques that improve the scalability, cost, latency, and throughput of production AI systems
• Help shape the technical vision and long-term roadmap for our foundational AI systems
• Own end-to-end architecture for complex AI systems, with attention to maintainability, observability, and ethical alignment
• Define and maintain AI reliability service-level objectives, including latency, uptime, and model-performance drift
• Collaborate with infrastructure engineering to improve GPU/TPU utilization and model-inference pipelines
• Lead technical reviews of AI deployments to ensure security, data governance, and compliance standards are met
• Mentor Principal and Senior Associates in scalable design, performance tuning, and translating research into production

Technologies:

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

More

We are Capital One, where we build responsible, reliable AI to improve banking. Our investments in technology, machine learning, and engineering support personalized customer experiences and scalable AI capabilities. You would join our Intelligent Foundations and Experiences team, which works across the company to advance AI science and engineering and deliver proprietary solutions used by millions of customers. The role is offered in Cambridge, Massachusetts; McLean, Virginia; New York, New York; and San Jose, California. Published annual salary ranges are $197,300–$225,100 in Cambridge and McLean, and $215,200–$245,600 in New York and San Jose; pay varies by work location. The position may also include performance-based incentives and comprehensive health, financial, and other benefits, subject to eligibility. We will consider sponsoring a qualified applicant for employment authorization.

last updated 43 week of 2026