AI Engineer 4, Gen AI Platform Services

Capital One Financial

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Quick summary

Work type: On-site
Location: San Francisco, CAMcLean, VACambridge, MASan Jose, CANew York, NY
Salary: $197,300–$225,100 / yr
Employment: Full-time
Posted: 14 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 $202k

This role $211k

$187k $230k

below market most similar roles pay here above market

This role pays more than 79% of similar roles. Most pay $192,050–$211,200 — the blue band above. At the midpoint, this role pays about $211k versus about $202k 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 4, Gen AI Platform Services

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The AI Engineer 4 (Gen AI Platform Services) joins the Intelligent Foundations and Experiences team to develop and deploy proprietary AI solutions central to the business. You will design, test, and support AI software components, including foundation model training, large language model inference, agents, multi-agent workflows, similarity search, guardrails, and model evaluation. The role involves owning end-to-end architecture for complex systems, defining service-level objectives for reliability, and optimizing GPU/TPU utilization. You will utilize a technical stack including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA, and Java. This position solves the technical challenge of building scalable, high-performance, and ethically aligned production AI systems that provide real-time, personalized customer experiences and automated internal workflows within a banking context.

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 Huggingface AWS Google Cloud Azure VectorDBs LLM Inference Distributed Systems Model Evaluation Observability

What you'll do

Design, develop, test, and deploy AI software components including LLM inference, agents, and multi-agent workflows.
Implement foundation model optimization techniques to improve scalability, cost, latency, and throughput of production 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 latency, 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 new AI deployments meet security, data governance, and compliance standards.
Mentor senior associates on scalable design, performance tuning, and translating research into production-ready systems.

What we're looking for

Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4 years of AI/ML experience.
Master's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 2 years of AI/ML experience.
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/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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