AI Engineer 4

Capital One Financial

Confirmed live yesterday Trusted

Quick summary

Work type
On-site
Location
San Jose, CAMcLean, VACambridge, MANew York, NY
Salary
$197,300–$225,100 / yr
Employment
Full-time
Posted
49 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $211k
This role $211k
$187k $235k
below market most similar roles pay here above market

This role pays more than 72% of similar roles. Most pay $192,050–$230,400 — the blue band above. At the midpoint, this role pays about $211k versus about $211k 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 2276 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1147 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · AI Engineer 4

JOB TITLE: AI Engineer 4 (AI Foundations, LLM Core and Agentic AI) The AI Engineer 4 (AI Foundations, LLM Core and Agentic AI) joins the Intelligent Foundations and Experiences team to develop proprietary AI solutions central to banking operations. You will design, develop, test, and deploy AI software components, including foundation model training, large language model inference, agents, multi-agent workflows, similarity search, guardrails, and model evaluation. You will own end-to-end architecture for complex systems, ensuring observability and ethical alignment while optimizing GPU/TPU utilization. The role requires proficiency in Python, Go, Scala, CUDA, or Java, alongside experience with AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch. You will solve technical problems regarding scalability, latency, and throughput for production AI systems, translating scientific research into reliable, high-performance infrastructure that powers real-time customer experiences and internal workflows.

What does a AI Engineer earn in California?

Median $246150 from 108 postings across 18 companies.

See salary data

What you'll do

  • Design, develop, test, and deploy AI software components including foundation model training and LLM inference.
  • Build and support agentic AI workflows, similarity search, guardrails, and model evaluation systems.
  • Implement state-of-the-art optimization techniques to improve scalability, cost, latency, and throughput of production AI systems.
  • Own the end-to-end architecture for complex AI systems to ensure maintainability, observability, and ethical alignment.
  • Define and maintain service-level objectives for AI reliability, including uptime and model performance drift.
  • Optimize GPU/TPU utilization and accelerate model inference pipelines in collaboration with infrastructure engineering.
  • Lead cross-functional technical reviews to ensure AI deployments meet security, data governance, and compliance standards.
  • Mentor senior associates on scalable design, performance tuning, and translating research into production.

What we're looking for

  • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of experience developing AI and ML algorithms.
  • Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 2 years of experience developing AI and ML algorithms.
  • At least 4 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).
  • 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (preferred).
  • Experience designing, developing, delivering, and supporting AI services (preferred).
  • Experience developing AI and ML algorithms 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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