Lead Engineer, Generative AI Product Engineering at Capital One
Charlottesville, VA
About the Job
Lead Engineer, Generative AI Product Engineering
Lead Engineer - Generative AI Product Engineering(Remote Eligible)
Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
We are looking for an experienced Lead 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.
Basic Qualifications:
Bachelor’s degree in Computer Science, Computer Engineering or a technical field
At least 6 years of experience designing and building data-intensive solutions using distributed computing and cache optimization techniques
At least 6 years of experience programming with Python, Go, Scala, or Java
At least 1 years 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.
Familiarity with deploying AI or ML models in demanding production environments.
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.
New York City (Hybrid On-Site): $201,400 - $229,900 for Lead Machine Learning Engineer
San Francisco and San Jose, California (Hybrid On-Site): $213,400 - $243,500 for Lead Machine Learning Engineer
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the
. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
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Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
