AI Engineer 5, AI Foundations

Capital One Financial

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Quick summary

Work type: On-site
Location: San Jose, CAMcLean, VACambridge, MANew York, NY
Salary: $229,900–$262,400 / yr
Employment: Full-time
Posted: 8 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $217k

This role $246k

$178k $271k

below market most similar roles pay here above market

This role pays more than 88% of similar roles. Most pay $186,900–$246,150 — the blue band above. At the midpoint, this role pays about $246k versus about $217k 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 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · AI Engineer 5, AI Foundations

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The AI Engineer 5 (AI Foundations) joins the Intelligent Foundations and Experiences team to develop responsible, scalable AI systems for banking. You will partner with cross-functional teams to design, develop, test, and deploy AI software components, including foundation model training, large language model inference, agents, multi-agent workflows, similarity search, and guardrails. Your daily work involves inventing optimization techniques to improve performance, scalability, and cost for production systems while leading cost-performance governance reviews and mentoring other engineers. You will utilize a technical stack including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA, and Java. The role focuses on solving complex technical problems by integrating LLMs and domain-specific models into unified production pipelines to enhance customer interactions and internal workflows.

What does a AI Engineer earn in California?

Median $246150 from 100 postings across 17 companies.

See salary data

Skills

Python Go Scala CUDA Java C++ C# PyTorch AWS Huggingface VectorDBs LLM Inference Similarity Search Multi-agent workflows Model Optimization Google Cloud Azure

What you'll do

Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
Implement multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models into unified systems.
Invent and introduce state-of-the-art optimization techniques to improve scalability, cost, latency, and throughput of production AI.
Establish and lead cost-performance governance reviews to track GPU utilization and inference cost efficiency.
Lead team design councils to ensure technical consistency and compliance with AI engineering standards.
Mentor Principal and Manager-level AI engineers to foster cross-domain learning and elevate organizational technical maturity.
Contribute to the technical vision and long-term roadmap of foundational AI systems.

What we're looking for

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field plus 6 years of AI/ML experience.
Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field plus 4 years of AI/ML experience.
At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.
Experience leading development of AI systems with tradeoff decisions around 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 VectorDBs using Python, C++, C#, Java, CUDA, or Golang (preferred).
Experience developing and applying state-of-the-art techniques for optimizing training and inference software (preferred).

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