This role pays more than
86%
of similar roles. Most pay
$156,350–$226,250
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$191k
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.
AI Engineer 5 joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions that enhance products for millions of customers. You will collaborate with cross-functional teams to design, test, and support software components including foundation model training, large language model inference, multi-agent workflows, similarity search, guardrails, and observability. The role involves optimizing performance metrics like scalability, cost, latency, and throughput while leading cost-performance governance reviews and mentoring other engineers. You will work with a technical stack featuring AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA, and Java. This position focuses on the core challenge of building responsible, scalable AI infrastructure to solve complex banking problems by integrating LLMs, vector search, and domain-specific models into unified production pipelines while ensuring technical consistency and compliance with engineering standards.
What does a AI Engineer earn in California?
Median $246150 from 73 postings across 11 companies.
Develop 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, and latency of production systems.
Design and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models.
Lead cost-performance governance reviews by tracking GPU utilization, model throughput, and inference efficiency.
Lead design councils to ensure technical consistency and compliance with AI engineering standards.
Mentor senior engineers to foster cross-domain learning and improve organizational technical maturity.
Translate complex research into production-ready features while ensuring ethical AI deployment and safety guardrails.
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
Python
Go
Scala
CUDA
C++
Java
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Model Optimization
Similarity Search
SaaS AI
Machine Learning
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Distributed Systems
C++
Java
Scala
C#
Machine Learning
Multi-agent Workflows
Similarity Search
Model Evaluation
Observability