This role pays more than
63%
of similar roles. Most pay
$184,975–$241,500
— the shaded band above.
At the midpoint, this role pays about
$211k
versus about
$213k
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.
AI Engineer 4 (AI Foundations, LLM Core and Agentic AI) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary solutions that power core business functions. You will collaborate with cross-functional teams to design, test, and support AI software components including foundation model training, large language model inference, agentic workflows, similarity search, guardrails, and model evaluation. The role involves optimizing performance metrics like latency, throughput, and cost while managing end-to-end architecture for complex systems. You will utilize a technical stack featuring PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. Required skills include proficiency in Python, Go, Scala, CUDA, or Java to build scalable infrastructure. The work focuses on solving high-impact problems in the banking sector by creating responsible, reliable AI systems that improve how customers interact with financial services and how internal associates perform their daily tasks.
What does a AI Engineer earn in New York?
Median $246150 from 63 postings across 10 companies.
Develop and deploy AI 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 end-to-end architectures for complex AI systems ensuring maintainability, observability, and ethical alignment.
Define and maintain service-level objectives for AI reliability including uptime and model performance drift.
Collaborate with infrastructure teams to optimize GPU/TPU utilization and accelerate inference pipelines.
Lead technical reviews to ensure new AI deployments meet 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 experience developing AI/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 2 years of experience developing AI/ML algorithms.
At least 4 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).
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 such as LLM inference, similarity search, vector databases, and guardrails using various programming languages (preferred).
Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost (preferred).
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
C++
Java
Scala
C#
Machine Learning
Model Evaluation
Similarity Search
SaaS
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
C++
Java
Scala
C#
Machine Learning
Model Optimization
Similarity Search
SaaS
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
C++
Java
Scala
C#
Machine Learning
Model Evaluation
Similarity Search
LLM
Python
PyTorch
Huggingface
CUDA
VectorDBs
AWS
Go
Scala
C++
Java
C#
Agentic AI
Model Optimization
Multi-agent Workflows
Similarity Search
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
SaaS
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Distributed Systems
C++
Java
Scala
C#
Machine Learning
Multi-agent Workflows
Similarity Search
Model Evaluation