below marketmost similar roles pay hereabove market
This role pays more than
72%
of similar roles. Most pay
$192,050–$220,750
— the blue band above.
At the midpoint, this role pays about
$211k
versus about
$206k
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
1891 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1020 roles with salary data.
The AI Engineer 4 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) joins the Intelligent Foundations and Experiences team to build and deploy proprietary AI solutions. You will design, develop, test, and support AI software components, including foundation model training, large language model inference, agents, multi-agent workflows, similarity search, guardrails, and model evaluation. The role involves inventing optimization techniques to improve performance, scalability, and cost for large-scale production systems while owning end-to-end architecture for maintainability and ethical alignment. You will utilize a stack including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA, and Java. This position solves technical challenges in creating responsible, scalable AI infrastructure, specifically focusing on model governance, observability, and optimizing GPU/TPU utilization for high-performance banking applications.
What does a AI Engineer earn in New York?
Median $228325 from 60 postings across 10 companies.
Design, develop, test, and deploy AI software components including LLM inference, agents, and multi-agent workflows.
Implement similarity search, guardrails, model evaluation, and observability for production AI systems.
Develop foundation model optimization techniques to improve scalability, cost, latency, and throughput.
Own the end-to-end architecture for complex AI systems to ensure maintainability and ethical alignment.
Define and maintain service-level objectives for AI reliability, including uptime and model performance drift.
Optimize GPU/TPU utilization and accelerate model inference pipelines in collaboration with infrastructure teams.
Lead cross-functional technical reviews to ensure 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 and ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 2 years of experience developing AI and ML algorithms.
At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience leading development of AI systems with tradeoff decisions around 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 and ML algorithms using Python, C++, C#, Java, CUDA, or Golang (preferred).
Experience developing and applying state-of-the-art techniques for optimizing training and inference software (preferred).
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Agentic AI
Distributed Systems
Similarity Search
GPU
TPU
Model Evaluation
Observability
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Distributed Systems
Similarity Search
Model Evaluation
Observability
Data Governance