This role pays more than
88%
of similar roles. Most pay
$159,225–$224,000
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$192k
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
878 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 872 roles with salary data.
As an AI Engineer 5 (AI Foundations) on the Intelligent Foundations and Experiences team, you will develop and deploy proprietary solutions that serve as core components for the company's business. You will collaborate with cross-functional teams to design, test, and support AI software including foundation model training, large language model inference, multi-agent workflows, similarity search, guardrails, and model evaluation. The role involves optimizing performance metrics like scalability, cost, latency, and throughput while leading cost-performance governance reviews for production systems. You will utilize a technical stack featuring PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. Required skills include proficiency in Python, Go, Scala, CUDA, or Java to build robust infrastructure. The work focuses on solving complex problems in the banking domain by creating responsible, scalable AI systems that enhance customer interactions and internal workflows.
What does a AI Engineer earn in California?
Median $246150 from 73 postings across 11 companies.
Design, develop, test, and deploy AI software components including foundation model training, LLM inference, and multi-agent workflows.
Implement state-of-the-art optimization techniques to improve performance, scalability, cost, latency, and throughput of production AI systems.
Build and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models into unified systems.
Lead cost-performance governance reviews by tracking GPU utilization, model throughput, and inference cost efficiency.
Lead design councils to ensure technical consistency and compliance with established AI engineering standards.
Mentor senior engineers to foster cross-domain learning and improve organizational technical maturity.
Translate complex scientific research into practical production techniques for large-scale banking applications.
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, CUDA, or Java.
Experience leading development of AI systems with trade-offs regarding cost, latency, throughput, and accuracy (preferred).
7 years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
Experience designing, developing, delivering, and supporting complex AI systems (preferred).
Experience developing AI/ML algorithms using Python, C++, C#, Java, CUDA, or Golang (preferred).
Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost (preferred).
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Similarity Search
C++
Scala
Java
C#
Model Optimization
Machine Learning
AI Engineering
LLM
Python
PyTorch
CUDA
Huggingface
VectorDBs
AWS
Go
Scala
C++
Java
C#
Agentic AI
Model Optimization
Multi-agent Workflows
Similarity Search
Machine Learning
LLM
Python
PyTorch
CUDA
Huggingface
VectorDBs
AWS
Go
Scala
C++
Java
C#
Agentic AI
Model Optimization
Multi-agent Workflows
Similarity Search
Machine Learning
LLM
Python
PyTorch
CUDA
Huggingface
VectorDBs
AWS
Go
Scala
C++
Java
C#
Agentic AI
Model Optimization
Multi-agent Workflows
Similarity Search
Machine Learning