This role pays more than
81%
of similar roles. Most pay
$170,000–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$208k
for comparable roles.
Based on 239 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.
As a Senior Lead AI Engineer (GenAI Platform Services, Agentic) within the Intelligent Foundations and Experiences team, you will partner with cross-functional teams of engineers, research scientists, and product managers to deliver AI-powered products. You will design, develop, test, deploy, and support critical software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, and observability. To achieve these goals, you will utilize a technical stack featuring AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch while implementing state-of-the-art LLM optimization techniques to improve performance metrics like latency and throughput. The role focuses on building scalable, high-performance AI infrastructure and proprietary solutions to solve complex problems in the banking domain, specifically aiming to enhance how customers interact with financial services through responsible and reliable machine learning systems.
Design, develop, test, and deploy AI software components including foundation model training and LLM inference.
Implement similarity search, guardrails, model evaluation, and observability for production AI 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, high-performance production features.
Lead and mentor engineering teams 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 algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI/ML algorithms.
At least 6 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, and supporting complex AI systems including LLM inference, similarity search, and vector databases.
Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost.
Ability to lead and mentor an engineering team while influencing cross-functional stakeholders.
Strong communication skills to articulate complex AI concepts clearly to peers.
Python
Go
Scala
Java
C++
C#
AWS
Huggingface
PyTorch
VectorDBs
LLM Inference
Nemo Guardrails
Machine Learning
Gen AI
Similarity Search
Model Evaluation
Observability
Python
Go
Scala
Java
C++
C#
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Nemo Guardrails
Machine Learning
Gen AI
Similarity Search
Model Evaluation
Observability
Python
Go
Scala
Java
C++
C#
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Nemo Guardrails
Machine Learning
Gen AI
Similarity Search
Model Evaluation
Observability