This role pays more than
60%
of similar roles. Most pay
$166,999–$246,150
— the shaded band above.
At the midpoint, this role pays about
$211k
versus about
$207k
for comparable roles.
Based on 240 similar postings.
Employer
About Capital One Financial
Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking
Capital One Financial currently has
998 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 992 roles with salary data.
Lead AI Engineer (GenAI Platform, AI Foundations, LLM Core and Agentic AI) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary solutions that power internal tools and customer-facing products. This role involves designing, testing, and supporting critical software components including foundation model training, large language model inference, similarity search, guardrails, and observability. You will collaborate with cross-functional teams to implement state-of-the-art LLM optimization techniques to improve performance metrics like latency, throughput, and cost for production systems. The technical stack includes Python, Go, Scala, Java, C++, C#, PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters. You will solve complex problems regarding the development of scalable, responsible AI infrastructure to enhance banking services through advanced machine learning models and high-performance systems that provide real-time, personalized experiences for customers.
Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
Implement similarity search, guardrails, model evaluation, experimentation, governance, and observability for production systems.
Develop state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, and throughput.
Utilize a broad stack of technologies including AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
Contribute to the technical vision and long-term roadmap of foundational AI systems.
Translate scientific research and novel techniques into practical production applications.
Solve complex, undefined problems by identifying root causes and providing clear technical solutions.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 2 years of experience developing AI/ML algorithms.
At least 4 years of experience programming with Python, Go, Scala, or Java.
Experience deploying scalable and responsible AI solutions on cloud platforms like AWS, Google Cloud, or Azure.
Experience designing, developing, delivering, and supporting AI services.
Experience developing AI and ML technologies including LLM inference, similarity search, vector databases, and guardrails.
Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost.
Ability to interpret scientific publications and apply novel research techniques in production environments.