This role pays more than
84%
of similar roles. Most pay
$161,500–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$204k
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.
AI Engineer 5 (MLX, Agentic AI, Gen AI platform Services) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions for banking services. This role involves designing, testing, and supporting software components including foundation model training, large language model inference, multi-agent workflows, similarity search, guardrails, and observability. The engineer will optimize production systems for performance, scalability, and cost while leading governance reviews regarding GPU utilization and inference efficiency. Key technical requirements include proficiency in Python, Go, Scala, CUDA, or Java, along with experience using PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The position focuses on solving complex problems in the banking domain by integrating LLMs and retrieval-augmented components into unified pipelines to improve customer interactions and internal workflows while ensuring high standards for ethical AI deployment and technical consistency across the organization.
What does a AI Engineer earn in California?
Median $246150 from 73 postings across 11 companies.
Develop and support AI software components including foundation model training, LLM inference, and multi-agent workflows.
Implement state-of-the-art optimization techniques to improve performance, scalability, cost, and latency of production systems.
Design and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models.
Lead cost-performance governance reviews by tracking GPU utilization, model throughput, and inference efficiency.
Lead design councils to ensure technical consistency and compliance with AI engineering standards.
Mentor senior engineers to foster cross-domain learning and improve organizational technical maturity.
Translate complex research into production-ready features for large-scale banking applications.
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/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI/ML algorithms.
At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience leading development of AI systems with trade-offs regarding 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/ML algorithms such as LLM inference, similarity search, and vector databases using various programming languages (preferred).
Experience optimizing training and inference software to improve hardware utilization and performance (preferred).
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Agentic AI
Multi-agent Workflows
Similarity Search
Model Evaluation
Model Optimization
C++
Scala
Java
C#
LLM
Python
PyTorch
CUDA
Huggingface
VectorDBs
AWS
Go
Scala
C++
Java
C#
Agentic AI
Model Optimization
Multi-agent Workflows
Similarity Search
Machine Learning
LLM
Python
PyTorch
CUDA
Huggingface
VectorDBs
AWS
Go
Scala
C++
Java
C#
Agentic AI
Model Optimization
Multi-agent Workflows
Similarity Search
Machine Learning