below marketmost similar roles pay hereabove market
This role pays more than
84%
of similar roles. Most pay
$186,900–$246,150
— the blue band above.
At the midpoint, this role pays about
$246k
versus about
$217k
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
2276 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1147 roles with salary data.
The AI Engineer 5 joins the Intelligent Foundations and Experiences team to develop responsible, scalable AI systems for banking. This role involves designing, developing, testing, and deploying AI software components, including foundation model training, large language model inference, agents, multi-agent workflows, similarity search, and guardrails. You will build multi-model orchestration pipelines, optimize performance for scalability and cost, and lead governance reviews for GPU utilization and inference efficiency. The position requires expertise in Python, Go, Scala, CUDA, or Java, alongside experience with PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. You will solve complex technical problems by integrating LLMs and domain-specific models into unified production systems while mentoring other engineers. The work focuses on creating high-performance AI infrastructure to enhance customer interactions and internal workflows.
What does a AI Engineer earn in California?
Median $246150 from 108 postings across 18 companies.
Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
Build and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models.
Implement state-of-the-art optimization techniques to improve scalability, cost, latency, and throughput of production AI systems.
Establish and lead cost-performance governance reviews to track GPU utilization and inference cost efficiency.
Lead design review boards to ensure technical consistency and compliance with AI engineering standards.
Mentor Principal and Manager-level AI engineers to foster cross-domain learning and elevate organizational technical maturity.
Contribute to the technical vision and long-term roadmap of foundational AI systems.
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 and ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI and ML algorithms.
At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience leading development of AI systems with tradeoff decisions around 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 and ML algorithms using Python, C++, C#, Java, CUDA, or Golang (preferred).
Experience developing and applying state-of-the-art techniques for optimizing training and inference software (preferred).
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Similarity Search
Multi-agent workflows
Model Evaluation
Observability
Google Cloud
Azure
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Similarity Search
Multi-agent workflows
Model Optimization
Google Cloud
Azure
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Similarity Search
Multi-agent workflows
Model Optimization
Google Cloud
Azure
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Similarity Search
Multi-agent workflows
Model Evaluation
Observability
Model Compression
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Similarity Search
Multi-agent workflows
Model Optimization
Google Cloud
Azure
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Similarity Search
Multi-agent workflows
Model Optimization
Google Cloud
Azure
Model Evaluation
Observability