This role pays more than
81%
of similar roles. Most pay
$162,000–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$204k
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
878 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 872 roles with salary data.
AI Engineer 5 (SDK's: Gen AI Evaluation and MCP) joins the Intelligent Foundations and Experiences team to develop responsible and reliable AI systems for banking applications. This role involves designing, developing, testing, and deploying AI software components including foundation model training, large language model inference, multi-agent workflows, similarity search, guardrails, and model evaluation. The engineer will optimize performance metrics like scalability, cost, latency, and throughput while leading cost-performance governance reviews and mentoring other engineers. The technical stack includes Python, Go, Scala, CUDA, Java, C++, C#, PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The work focuses on building high-performance AI infrastructure and multi-model orchestration pipelines to solve complex problems in the banking domain, specifically by integrating LLMs and retrieval-augmented components into unified systems to improve how customers interact with financial services.
What does a AI Engineer earn in Virginia?
Median $246150 from 60 postings across 4 companies.
Design, develop, test, 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, latency, and throughput of production systems.
Build and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models into unified systems.
Lead cost-performance governance reviews by tracking GPU utilization, model throughput, and inference cost efficiency.
Lead design councils to ensure technical consistency and compliance with established AI engineering standards.
Mentor senior engineers to foster cross-domain learning and improve organizational technical maturity.
Translate complex research papers into practical production techniques for large-scale 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 using Python, C++, C#, Java, CUDA, or Golang (preferred).
Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost (preferred).
Python
Go
Scala
CUDA
C++
Java
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Model Optimization
Similarity Search
SaaS AI
Machine Learning
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Similarity Search
C++
Scala
Java
C#
Model Optimization
Machine Learning
AI Engineering