below marketmost similar roles pay hereabove market
This role pays more than
79%
of similar roles. Most pay
$192,050–$211,200
— the blue band above.
At the midpoint, this role pays about
$211k
versus about
$202k
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
2107 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1107 roles with salary data.
The AI Engineer 4 (LLM Gateway, FM Hosting) joins the Intelligent Foundations and Experiences team to build and deploy proprietary AI solutions. You will design, develop, test, 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 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 engineering to optimize GPU/TPU utilization. This position solves technical problems regarding responsible, scalable AI infrastructure and model governance within a banking context.
What does a AI Engineer earn in California?
Median $246150 from 100 postings across 17 companies.
Design, develop, test, deploy, and support AI software components including LLM inference, agents, and multi-agent workflows.
Invent and introduce state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput.
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 for new AI system deployments to ensure security, data governance, and compliance.
Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field plus 4 years of experience developing AI and ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field 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
Distributed Systems
Model Evaluation
Observability
GPU
TPU
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Distributed Systems
Similarity Search
Model Evaluation
Observability
Data Governance
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Similarity Search
Multi-agent workflows
Model Optimization
Model Evaluation
Observability
GPU Utilization