below marketmost similar roles pay hereabove market
This role pays more than
84%
of similar roles. Most pay
$192,225–$284,962
— the blue band above.
At the midpoint, this role pays about
$288k
versus about
$239k
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
2204 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1138 roles with salary data.
The Director AI Engineer joins the Intelligent Foundations and Experiences team to lead the development of responsible, scalable AI systems for banking. You will oversee the design, development, testing, and deployment of AI software components, including foundation model training, large language model inference, similarity search, guardrails, and model evaluation. Key responsibilities include making build-vs-buy decisions, inventing optimization techniques for performance and cost, and establishing enterprise standards for Responsible AI. You will utilize a technical stack including AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch, while potentially using Python, C++, C#, Java, CUDA, or Golang. This role solves complex problems regarding production AI scalability, governance, and audit readiness, translating enterprise strategy into execution plans that deliver high-leverage impact across multiple product areas and customer-facing applications.
Oversee the design, development, testing, deployment, and support of AI software components including LLM inference and foundation model training.
Make high-judgment build-vs-buy decisions regarding open-source and SaaS AI technologies like AWS Ultraclusters and VectorDBs.
Invent and introduce state-of-the-art optimization techniques to improve the performance, cost, and latency of production AI systems.
Translate enterprise AI strategy into portfolio-level execution plans across multiple product areas while balancing innovation with delivery discipline.
Scale AI engineering practices through shared infrastructure, reusable components, and unified observability and governance frameworks.
Establish enterprise standards for Responsible AI, including fairness metrics, model evaluation protocols, and audit readiness.
Partner with research, compliance, and risk teams to ensure deployed systems meet ethical and regulatory standards.
Attract, retain, and nurture the professional development of top AI engineering talent.
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 and ML algorithms.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 6 years of experience developing AI and ML algorithms.
At least 3 years of people leadership experience.
5+ years of experience managing and leading an engineering team (preferred).
7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
Experience developing AI and ML algorithms using Python, C++, C#, Java, CUDA, or Golang (preferred).
Experience building and leading multi-team AI organizations delivering multiple enterprise products concurrently (preferred).
Experience establishing cross-functional operating rhythms and review cadences such as OKRs and AI governance councils (preferred).
Remote (San Francisco, CA)+536 days ago
$244,700–$279,200
Python
C++
Java
CUDA
Golang
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Similarity Search
Agentic AI
Observability
Governance
Responsible AI
LLM Inference
Agentic AI
PyTorch
VectorDBs
Huggingface
Python
C++
CUDA
Golang
Java
C#
AWS
Google Cloud
Azure
MLOps
Similarity Search
Model Evaluation
Observability
Guardrails
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
AWS
Huggingface
VectorDBs
LLM Inference
Similarity Search
Multi-agent workflows
Model Evaluation
Observability
Google Cloud
Azure
Python
Go
Scala
CUDA
Java
C++
C#
PyTorch
Huggingface
AWS
Google Cloud
Azure
VectorDBs
LLM Inference
Similarity Search
Multi-agent workflows
Model Evaluation
Observability
Model Compression