This role pays more than
86%
of similar roles. Most pay
$162,000–$247,053
— the shaded band above.
At the midpoint, this role pays about
$262k
versus about
$205k
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
1554 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 796 roles with salary data.
Staff AI Engineer - Enterprise Analysis Platform joins the Intelligent Foundations and Experiences team to build an AI-native platform for enterprise data analysis. This role involves designing, developing, testing, and deploying AI software components including foundation model training, large language model inference, multi-agent workflows, similarity search, guardrails, and observability. The engineer will implement state-of-the-art optimization techniques to improve performance metrics like scalability, cost, latency, and throughput for production systems. Key responsibilities include setting technical direction for enterprise architecture, managing model routing, and ensuring responsible AI principles. The role requires proficiency in Python, Go, Scala, CUDA, or Java, alongside experience with PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The position addresses the challenge of integrating deterministic code with non-deterministic reasoning systems to transform how internal associates perform data analysis across various business lines.
What does a AI Engineer earn in California?
Median $246150 from 78 postings across 11 companies.
Design, develop, test, and deploy AI software components including LLM inference, agentic workflows, and similarity search.
Implement foundation model optimization techniques to improve performance, scalability, cost, and latency for production systems.
Establish enterprise-wide AI architecture standards for tooling, observability, and deployment across multiple teams.
Manage the integration of model routing, caching, and orchestration systems for hybrid and multi-model workloads.
Embed responsible AI principles including transparency, reproducibility, and fairness into all system designs.
Drive internal education and mentorship through architecture councils and AI guilds to share best practices.
Translate complex research papers into practical production techniques for large-scale enterprise applications.
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).
Experience developing AI/ML algorithms such as LLM inference, similarity search, vector databases, and guardrails using various programming languages (preferred).
Experience applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization and performance (preferred).