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This listing doesn't post a salary. Most similar roles pay
$192,050–$230,400.
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 4 joins the Intelligent Foundations and Experiences team to develop responsible and reliable AI systems 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. Key responsibilities include owning end-to-end architecture for complex systems, defining service-level objectives for reliability, and optimizing GPU/TPU utilization. You will leverage a technical stack including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA, and Java. The role focuses on solving technical challenges related to scalability, cost, latency, and throughput while ensuring ethical alignment, data governance, and security for production AI systems that power personalized customer experiences and internal associate workflows.
What does a AI Engineer earn in California?
Median $246150 from 108 postings across 18 companies.
Design, develop, test, and deploy AI software components including LLM inference, multi-agent workflows, and guardrails.
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 uptime and model performance drift.
Optimize GPU/TPU utilization and accelerate model inference pipelines in collaboration with infrastructure engineering.
Lead technical reviews for new AI deployments to ensure security, data governance, and compliance standards.
Mentor senior associates on scalable design, performance tuning, and translating research into production.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of AI/ML experience.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 2 years of AI/ML experience.
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/ML algorithms like LLM Inference, Similarity Search, and VectorDBs using Python, C++, C#, Java, CUDA, or Golang (preferred).
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization (preferred).
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Agentic AI
Similarity Search
Model Evaluation
Model Optimization
Google Cloud
Azure
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 Workflows
Distributed Systems
Model Evaluation
Observability