This role pays more than
81%
of similar roles. Most pay
$162,000–$211,200
— the shaded band above.
At the midpoint, this role pays about
$211k
versus about
$187k
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 4 on the Intelligent Foundations and Experiences team, you will develop and deploy proprietary AI solutions that serve as core components for the company's business operations. 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. Your daily work involves optimizing performance metrics like latency and throughput while ensuring ethical alignment and governance. You will utilize a technical stack featuring PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The role requires proficiency in Python, Go, Scala, CUDA, or Java to build scalable systems for the banking sector. You will also mentor other associates on research-to-production translation while managing complex architectures to solve high-impact problems in automated customer interactions and internal workflows.
What does a AI Engineer earn in New York?
Median $246150 from 63 postings across 10 companies.
Develop and deploy AI software components including foundation model training, LLM inference, and multi-agent workflows.
Implement optimization techniques to improve performance, scalability, cost, latency, and throughput for large-scale production systems.
Design end-to-end architecture for complex AI systems ensuring maintainability, observability, and ethical alignment.
Define and maintain service-level objectives (SLOs) 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 for hardware utilization, latency, throughput, and cost (preferred).
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
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
C++
Java
Scala
C#
Machine Learning
Model Evaluation
Similarity Search
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
Multi-agent Workflows
Similarity Search
C++
Scala
Java
C#
Model Optimization
Machine Learning
AI Engineering