Full-Time Senior Generative AI Product Engineer

We are looking for an experienced Senior Generative AI Engineer to help build and maintain APIs and SDKs to train, fine-tune and access AI models at scale. You will work as part of our Enterprise AI team and build systems that will enable our users to work with Large-Language Models (LLMs) and Foundation Models (FMs), using our public cloud infrastructure.  You will work with a team of world-class AI engineers and researchers  to design and implement key API products and services that enable real-time customer-facing applications.  Examples of projects you will work on include: 

• Architect, build and deploy well-managed core APIs and SDKs to access LLMs and our proprietary FMs including training, fine-tuning and prompting tasks, including orchestration SDKs. 
• Design APIs for performance, real-time applications, scale, ease of use and governance automation. 
• Develop application-specific interfaces that leverage LLMs and FMs to continue to enhance the associate and customer experience.
• Enable our users to build new GenAI capabilities. 
• Develop tools and processes to monitor API access patterns and operational health.
• Design and implement AI safety and guardrails in the API layer working closely with researchers. 

Capital One is open to hiring a Remote Employee for this opportunity

Basic Qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering or a technical field
• At least 4 years of experience designing and building and deploying ML application platforms.
• At least 4  years of experience programming with Python, Go, Scala, or Java
• At least 1  year of experience building, scaling, and optimizing training or inferencing systems for  deep neural networks 

Preferred Qualifications:

• Familiarity with building large-scale AI and ML products or platforms serving millions of users. 
• Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP.
• Experience with Kubernetes and KubeFlow workloads is preferred.
• Familiarity with the Model Development Lifecycle and MLOps preferred.
• Experience architecting cloud systems for security, availability, performance, scalability, and cost.
• Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. 
• Experience at tech and product-driven companies/startups preferred. 
• Ability to iterate rapidly with researchers and engineers to improve a product experience while building the foundational capabilities.
• Have experience with API security, observability, cloud access control and privacy best practices. 

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.