This role pays less than
70%
of similar roles. Most pay
$139,518–$196,750
— the shaded band above.
At the midpoint, this role pays about
$145k
versus about
$168k
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
878 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 872 roles with salary data.
As an AI Engineer 2 on the Intelligent Foundations and Experiences team, you will collaborate with cross-functional partners to develop and deploy proprietary AI solutions that enhance internal workflows and customer interactions. You will design, test, and support critical software components including foundation model training, large language model inference, multi-agent workflows, similarity search, guardrails, and model evaluation. The role involves optimizing performance metrics like latency, throughput, and cost for large-scale production systems while contributing to the technical roadmap of foundational AI infrastructure. You will utilize a technology stack featuring PyTorch, Huggingface, VectorDBs, AWS Ultraclusters, and programming languages such as Python, Go, Scala, CUDA, or Java. Your work focuses on solving complex problems in banking by building responsible, scalable systems that integrate advanced techniques like retrieval-augmented generation and agentic AI observability to provide high-quality, safe customer experiences.
What does a AI Engineer earn in California?
Median $246150 from 73 postings across 11 companies.
Design, develop, test, and deploy AI software components including foundation model training and LLM inference.
Implement multi-agent workflows, similarity search, guardrails, and automated regression tests for production models.
Develop optimization techniques to improve performance metrics like scalability, cost, latency, and throughput for large-scale systems.
Build deployment pipelines, testing environments, and telemetry systems to ensure operational readiness of AI products.
Create high-quality prompts and evaluation datasets to ensure safe and reliable model outputs.
Establish internal engineering standards for reproducibility, monitoring, and ethical deployment of AI technologies.
Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 2 years of experience developing AI/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields.
At least 2 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience contributing to development of components of AI systems with tradeoff decisions around cost, latency, throughput and accuracy (preferred).
2 years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
Experience developing, delivering, and supporting AI components (preferred).
Experience developing AI and ML algorithms or technologies 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, latency, throughput, and cost (preferred).
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Similarity Search
C++
Scala
Java
C#
Model Optimization
Machine Learning
AI Engineering
Python
Go
Scala
CUDA
C++
C#
Java
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Model Evaluation
Model Optimization
Machine Learning
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Distributed Systems
C++
Java
Scala
C#
Machine Learning
Multi-agent Workflows
Similarity Search
Model Evaluation
Observability
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Distributed Systems
C++
Java
Scala
C#
Machine Learning
Multi-agent Workflows
Similarity Search
Model Evaluation