This role pays more than
85%
of similar roles. Most pay
$173,200–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$210k
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
836 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 829 roles with salary data.
As an AI Engineer 5 ((AI Foundations, LLM Core and Agentic AI), you will join the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions that power core business functions. You will collaborate with cross-functional teams to design, test, and support 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 while managing governance reviews for GPU utilization. You will work with a technical stack featuring PyTorch, Huggingface, VectorDBs, AWS Ultraclusters, Python, Go, Scala, CUDA, and Java. Your work focuses on the technical challenge of building scalable, high-performance AI infrastructure and multi-model orchestration pipelines to integrate LLMs and domain-specific models into unified systems for banking applications.
What does a AI Engineer earn in New York?
Median $246150 from 63 postings across 10 companies.
Develop and support AI components including foundation model training, LLM inference, agentic workflows, and guardrails.
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.
Contribute to the long-term technical vision and roadmap for foundational AI systems.
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 like 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).
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
LLM
Python
PyTorch
CUDA
Huggingface
VectorDBs
AWS
Go
Scala
C++
Java
C#
Agentic AI
Model Optimization
Multi-agent Workflows
Similarity Search
Machine Learning