This role pays more than
85%
of similar roles. Most pay
$176,950–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$212k
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.
Senior Lead AI Engineer (Gen AI Platform Services: Distributed Systems) joins the Intelligent Foundations and Experiences team to develop proprietary solutions for large-scale production AI systems. This role involves collaborating with cross-functional teams to design, test, deploy, and support critical software components including foundation model training, large language model inference, similarity search, guardrails, and observability. The engineer will invent state-of-the-art LLM optimization techniques to improve performance metrics like latency, throughput, and cost while contributing to the long-term technical roadmap of foundational systems. The role requires proficiency in Python, Go, Scala, or Java, alongside experience with PyTorch, Huggingface, VectorDBs, Nemo Guardrails, and AWS Ultraclusters. This position addresses the challenge of building responsible, scalable AI infrastructure to enhance internal workflows and customer interactions within the banking sector by translating complex research into production-ready technologies.
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 complex scientific research into practical production techniques for large-scale AI infrastructure.
Lead and mentor an engineering team while influencing cross-functional stakeholders on AI initiatives.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 6 years of experience developing AI/ML technologies.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI/ML technologies.
At least 6 years of experience programming with Python, Go, Scala, or Java.
7 years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
Experience designing, developing, integrating, delivering, and supporting complex AI systems (preferred).
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders (preferred).
Experience developing AI/ML algorithms like LLM Inference, Similarity Search, and VectorDBs using Python, C++, C#, Java, or Golang (preferred).
Experience applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost (preferred).
Python
Go
Scala
Java
C++
C#
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Nemo Guardrails
Machine Learning
Gen AI
Similarity Search
Model Evaluation
Observability