below marketmost similar roles pay hereabove market
This role pays more than
70%
of similar roles. Most pay
$192,050–$230,400
— the blue band above.
At the midpoint, this role pays about
$211k
versus about
$211k
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
2229 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1126 roles with salary data.
AI Engineer 4 (Gen AI Platform Services: Agentic Systems) joins the Intelligent Foundations and Experiences team to develop proprietary AI solutions for banking. You will design, develop, test, deploy, and support AI software components, including foundation model training, large language model inference, agents, multi-agent workflows, similarity search, guardrails, and model evaluation. The role involves inventing optimization techniques to improve performance, scalability, cost, and latency for large-scale production systems. You will utilize a technical stack including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA, and Java. Key responsibilities include owning end-to-end architecture, defining service-level objectives for reliability, and collaborating with infrastructure teams to optimize GPU/TPU utilization. You will solve complex problems regarding model governance, observability, and ethical alignment within a high-performance AI infrastructure.
What does a AI Engineer earn in California?
Median $246150 from 105 postings across 18 companies.
Design, develop, test, deploy, and support AI software components including LLM inference, agents, and multi-agent workflows.
Implement foundation model optimization techniques to improve scalability, cost, latency, and throughput of production systems.
Own the end-to-end architecture for complex AI systems to ensure maintainability, observability, and ethical alignment.
Define and maintain service-level objectives for AI reliability, including latency, uptime, and model performance drift.
Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
Lead cross-functional technical reviews to ensure new AI deployments meet security, data governance, and compliance standards.
Mentor senior associates on scalable design, performance tuning, and translating research into production environments.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI and ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 2 years of experience developing AI and ML algorithms.
At least 4 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).
6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
Experience designing, developing, delivering, and supporting AI services (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
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Kubernetes
Huggingface
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Model Evaluation
Observability