This role pays more than
85%
of similar roles. Most pay
$173,025–$246,150
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$210k
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.
AI Engineer 5 (AI Foundations, LLM Core and Agentic AI) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions that enhance customer interactions and internal workflows. 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 optimize performance metrics like latency, throughput, and cost while managing governance reviews for GPU utilization and infrastructure. Key technologies include Python, Go, Scala, CUDA, Java, C++, C#, PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The position focuses on the technical challenge of building scalable, high-performance AI systems by integrating LLMs and retrieval-augmented components into unified production pipelines to solve complex problems in the banking domain through advanced model orchestration and state-of-the-art optimization techniques.
What does a AI Engineer earn in Virginia?
Median $246150 from 55 postings across 4 companies.
Develop and deploy 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 papers into practical production techniques for large-scale 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 like LLM inference, similarity search, and vector databases using various programming languages (preferred).
Experience optimizing training and inference software to improve hardware utilization and performance (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