This role pays more than
84%
of similar roles. Most pay
$168,900–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$208k
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 (GenAI Platform, Agentic Infrastructure) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary solutions that power core business functions. You will collaborate with cross-functional teams of engineers, scientists, and product managers to build AI-powered products while designing, testing, and supporting software components including foundation model training, large language model inference, similarity search, guardrails, and observability. The role involves implementing state-of-the-art LLM optimization techniques to improve performance metrics like scalability, cost, latency, and throughput for production systems. You will utilize a technical stack featuring AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch. Required skills include proficiency in Python, Go, Scala, or Java, along with expertise in machine learning algorithms and infrastructure to solve complex problems within the banking domain by creating scalable, high-performance AI systems for customer and associate interactions.
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 Huggingface, VectorDBs, PyTorch, and AWS Ultraclusters.
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 with at least 6 years of experience developing AI and ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 4 years of experience developing AI and 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 such as AWS, Google Cloud, or Azure.
Experience designing, developing, integrating, delivering, and supporting complex AI systems including LLM inference, similarity search, and guardrails.
Experience applying state-of-the-art techniques to optimize training and inference software for hardware utilization, latency, throughput, and cost.
Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders.
Excellent communication skills with the ability to articulate complex AI concepts to peers.
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#
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