AI Engineer IV

Capital One Financial

Confirmed live today High trust

Quick summary

Work type
On-site
Location
McLean, VASan Francisco, CACambridge, MASan Jose, CANew York, NY
Salary
$197,300–$225,100 / yr
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $208k
This role $211k
$164k most similar roles pay here $251k

This role pays more than 64% of similar roles. Most pay $172,500–$242,662 — the shaded band above. At the midpoint, this role pays about $211k versus about $208k 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 836 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 829 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · AI Engineer IV

AI Engineer 4 (MLX, Agentic AI, Gen AI platform Services) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions that enhance products for millions of customers. This role involves designing, testing, and supporting software components including foundation model training, large language model inference, agentic workflows, similarity search, guardrails, and model evaluation. The engineer will optimize performance metrics like latency, throughput, and cost while managing end-to-end architecture for complex systems. Key technical requirements include proficiency in Python, Go, Scala, CUDA, or Java, alongside experience with PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters. The position focuses on solving the challenge of building scalable, high-performance AI infrastructure and ensuring ethical alignment and governance within a banking context to provide reliable, real-time customer experiences through advanced machine learning technologies and innovative model optimization techniques.

What does a AI Engineer earn in Virginia?

Median $246150 from 55 postings across 4 companies.

See salary data

What you'll do

  • Design, develop, test, and deploy AI software components including foundation model training and LLM inference.
  • Build agentic AI systems and multi-agent workflows using tools like Huggingface and VectorDBs.
  • Implement optimization techniques to improve performance, scalability, cost, and latency for large-scale production systems.
  • Own the end-to-end architecture for complex AI systems ensuring maintainability, observability, and ethical alignment.
  • Define and maintain service-level objectives (SLOs) for AI reliability including uptime and model performance drift.
  • Collaborate with infrastructure teams to optimize GPU/TPU utilization and accelerate inference pipelines.
  • Lead technical reviews to ensure new 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/ML algorithms.
  • Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 2 years of experience developing AI/ML algorithms.
  • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java.
  • Experience leading development of AI systems with trade-offs regarding 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/ML algorithms using Python, C++, C#, Java, CUDA, or Golang (preferred).
  • Experience building agentic AI systems and workflows (preferred).

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