below marketmost similar roles pay hereabove market
This role pays more than
86%
of similar roles. Most pay
$170,000–$246,150
— the blue 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
1917 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1045 roles with salary data.
JOB TITLE: AI Engineer 5
The AI Engineer 5 joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions central to the business. This role involves partnering with cross-functional teams to design, test, and support AI software components, including foundation model training, large language model inference, agents, multi-agent workflows, similarity search, and guardrails. You will invent optimization techniques to improve performance, scalability, and cost for large-scale production systems while leading cost-performance governance reviews and mentoring other engineers. The role requires proficiency in Python, Go, Scala, CUDA, or Java, alongside experience with AWS Ultraclusters, Huggingface, and VectorDBs. You will solve complex technical problems by integrating LLMs and domain-specific models into unified production pipelines to deliver responsible, high-performance AI infrastructure for banking services.
What does a AI Engineer earn in California?
Median $246150 from 84 postings across 12 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 councils and 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 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
Model Compression
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Multi-agent workflows
Similarity Search
Model Evaluation
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
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Similarity Search
Multi-agent workflows
Model Evaluation
Observability
Google Cloud
Azure