This role pays more than
79%
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
886 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 880 roles with salary data.
Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) joins the Intelligent Foundations and Experiences team to develop responsible, scalable AI systems for banking services. This role involves overseeing the design, development, testing, and deployment of critical software components including foundation model training, large language model inference, similarity search, guardrails, and model evaluation. You will manage a multi-disciplinary team to translate enterprise goals into actionable roadmaps while making build-vs-buy decisions across technologies like AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch. The position requires expertise in Python, C++, C#, Java, CUDA, or Golang to optimize performance metrics such as latency and throughput. You will solve complex problems regarding model lifecycle management, MLOps, and AI observability while ensuring production systems meet strict governance standards for reliability and compliance within the financial services domain.
Oversee the design, development, testing, deployment, and support of AI software components including LLM inference and guardrails.
Make high judgment build-vs-buy decisions regarding open source and SaaS AI technologies like Huggingface and VectorDBs.
Implement state-of-the-art foundation model optimization techniques to improve performance, scalability, cost, and latency in production systems.
Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular reporting.
Operationalize Responsible AI by establishing review gates, documentation requirements, and rollout standards for all production systems.
Manage the end-to-end lifecycle of AI models through collaboration with Research, Data, and Platform teams.
Lead, mentor, and develop a team of engineers and scientists to productize prototypes and meet production SLOs.
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 1 year of people leadership experience.
3 years of experience managing and leading an engineering team (preferred).
6 years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
Experience developing AI and ML technologies like LLM Inference, Similarity Search, and VectorDBs using Python, C++, C#, Java, CUDA, or Golang (preferred).
Experience building agentic AI systems and workflows (preferred).
Experience leading technical strategy for multi-disciplinary teams and mentoring engineers to productize prototypes (preferred).
Python
Go
CUDA
PyTorch
Huggingface
AWS
VectorDBs
LLM Inference
Agentic AI
Multi-agent Workflows
Similarity Search
Model Evaluation
Model Optimization
C++
Scala
Java
C#
LLM
Python
PyTorch
CUDA
Huggingface
VectorDBs
AWS
Go
Scala
C++
Java
C#
Agentic AI
Model Optimization
Multi-agent Workflows
Similarity Search
Machine Learning