AI Engineer 4, Gen AI Platform Services: Agentic AI

Capital One Financial

Confirmed live today High trust

Quick summary

Work type: On-site
Location: New York, NYSan Francisco, CAMcLean, VACambridge, MASan Jose, CA
Salary: $197,300–$225,100 / 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 $211k

This role $211k

$187k $235k

below market most similar roles pay here above market

This role pays more than 71% 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 2232 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1142 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: Agentic AI

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The AI Engineer 4 (Gen AI Platform Services: Agentic AI) joins the Intelligent Foundations and Experiences team to develop proprietary AI solutions for banking. You will design, develop, test, deploy, 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 inventing optimization techniques to improve performance, scalability, cost, and latency for large-scale production systems. You will utilize a stack including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA, and Java. Key responsibilities include owning end-to-end architecture, defining service-level objectives for reliability, and collaborating with infrastructure engineering to optimize GPU/TPU utilization. You will solve complex technical problems regarding model governance, observability, and ethical alignment within a high-performance AI infrastructure.

What does a AI Engineer earn in New York?

Median $246150 from 71 postings across 9 companies.

See salary data

Skills

Python Go Scala CUDA Java C++ C# PyTorch AWS Kubernetes Huggingface VectorDBs LLM Inference Agentic AI Distributed Systems Model Evaluation Observability

What you'll do

Design, develop, test, deploy, and support AI software components including LLM inference 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 environments.

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).
3+ years of experience with Kubernetes (preferred).
Experience designing, developing, delivering, and supporting AI services (preferred).
Experience developing AI/ML algorithms using Python, C++, C#, Java, CUDA, or Golang (preferred).

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