This role pays more than
76%
of similar roles. Most pay
$211,200–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$229k
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
1756 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 951 roles with salary data.
AI Engineer 5 (FM Hosting, LLM Inference) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions that enhance products for millions of customers. This role involves designing, testing, and supporting software components including foundation model training, large language model inference, multi-agent workflows, similarity search, guardrails, and model evaluation. The engineer will implement state-of-the-art optimization techniques to improve performance metrics like scalability, cost, latency, and throughput for production systems. Key responsibilities include managing cost-performance governance reviews and mentoring other engineers. The role requires proficiency in Python, Go, Scala, CUDA, or Java, alongside experience with PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The work focuses on building high-performance AI infrastructure and multi-model orchestration pipelines to solve complex problems regarding large-scale production systems and automated agentic workflows within the banking sector.
What does a AI Engineer earn in Virginia?
Median $246150 from 65 postings across 4 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 while ensuring ethical AI deployment and guardrails.
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 developing AI/ML algorithms such as LLM inference, similarity search, vector databases, and guardrails (preferred).
Experience optimizing training and inference software to improve hardware utilization and performance (preferred).
Experience building agentic AI systems and workflows (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