This role pays more than
97%
of similar roles. Most pay
$170,987–$246,000
— the shaded band above.
At the midpoint, this role pays about
$288k
versus about
$208k
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
939 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 936 roles with salary data.
Staff AI Engineer joins the Intelligent Foundations and Experiences team to develop responsible, scalable AI systems for banking applications. This role involves designing, developing, testing, and deploying software components including foundation model training, large language model inference, multi-agent workflows, similarity search, guardrails, and observability tools. The engineer will also define enterprise-wide architecture standards, optimize performance metrics like latency and throughput, and manage model routing and orchestration systems. Key technical requirements include proficiency in Python, Go, Scala, CUDA, or Java, alongside experience with PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The position focuses on solving complex problems related to high-performance AI infrastructure and ensuring fairness-by-design. By integrating state-of-the-art research into production environments, the role aims to improve how customers interact with banking services through advanced machine learning technologies and robust engineering practices.
What does a AI Engineer earn in Virginia?
Median $246150 from 61 postings across 4 companies.
Design, develop, test, and deploy AI software components including foundation model training and LLM inference.
Implement agentic workflows, similarity search, guardrails, and observability for large-scale production systems.
Develop optimization techniques to improve performance metrics such as cost, latency, throughput, and scalability.
Establish enterprise-wide AI architecture standards for tooling, deployment, and governance across multiple teams.
Design and integrate model routing, caching, and orchestration systems for hybrid and multi-model workloads.
Incorporate responsible AI principles including transparency, reproducibility, and fairness into all system designs.
Drive internal education and mentorship through architecture councils and AI guilds.
Translate complex research papers into practical production techniques to solve undefined business problems.
What we're looking for
Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 8 years of experience developing AI/ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 6 years of experience developing AI/ML algorithms.
At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy (preferred).
8 years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems (preferred).
Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level (preferred).
Experience developing AI/ML algorithms using Python, C++, C#, Java, CUDA, or Golang (preferred).
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Similarity Search
C++
Scala
Java
C#
Model Optimization
Machine Learning
AI Engineering
Python
Go
Scala
CUDA
C++
C#
Java
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Model Evaluation
Model Optimization
Machine Learning