This role pays more than
83%
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.
As an AI Engineer 5 (AI Foundations, LLM Core and Agentic AI) on the Intelligent Foundations and Experiences team, you will develop and deploy proprietary solutions that power core business functions. You will collaborate with cross-functional teams to design, test, and support AI software components including foundation model training, large language model inference, agentic workflows, similarity search, guardrails, and observability. The role involves optimizing performance metrics like scalability, cost, latency, and throughput for production systems while leading governance reviews for GPU utilization and inference efficiency. You will utilize a technical stack featuring PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. Required skills include proficiency in Python, Go, Scala, CUDA, or Java to build multi-model orchestration pipelines. This role addresses the challenge of creating responsible, scalable AI systems to enhance customer interactions and internal workflows within the banking sector.
What does a AI Engineer earn in Massachusetts?
Median $246150 from 58 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 review boards 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, high-performing production features.
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 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
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Multi-agent Workflows
Similarity Search
C++
Scala
Java
C#
Model Optimization
Machine Learning
AI Engineering