Principal Software Engineer, AI Engineer

JPMorgan Chase

Quick summary

Work type
On-site
Location
Jersey City, NJPalo Alto, CAWilmington, DE
Salary
$204,250–$285,000 / yr
Posted
2 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $196k
This role $245k
$128k most similar roles pay here $302k

This role pays more than 85% of similar roles. Most pay $167,100–$225,175 — the shaded band above. At the midpoint, this role pays about $245k versus about $196k for comparable roles.

Based on 239 similar postings.

Employer

About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 436 open roles on FindRole.

Listed pay typically runs $152,000–$215,000 across 230 roles with salary data.

Most-posted roles

View all roles at JPMorgan Chase

At a glance

TL;DR · Principal Software Engineer, AI Engineer

As a Principal Software Engineer at JPMorgan Chase within the Corporate Sector’s AI/ML & Data Platforms team, you will lead and mentor a specialized group of engineers to develop high-quality, scalable machine learning solutions. Your daily responsibilities include designing agentic AI reference architectures, implementing production-quality Python code using frameworks like PyTorch or TensorFlow, and creating reusable components for prompt management and safety filters. You will also build LLM-powered APIs and microservices, manage the end-to-end ML lifecycle, and optimize inference performance. Additionally, you will collaborate with data teams on structured and unstructured data pipelines and set engineering standards for agentic AI systems, ensuring operational excellence and adherence to responsible AI practices in a regulated financial environment.

What you'll do

  • Design and implement agentic AI reference architectures for complex projects.
  • Write and review production-quality Python code using PyTorch or TensorFlow.
  • Create reusable components for prompt management, evaluators, and safety filters.
  • Build and operate LLM-powered APIs and microservices in advisor workflows.
  • Own the end-to-end ML lifecycle including CI/CD, automated testing, and monitoring.
  • Optimize inference processes for latency, throughput, and cost efficiency.
  • Set engineering standards and lead design reviews for agentic AI systems.

What we're looking for

  • Deep expertise in Python engineering with hands-on experience using PyTorch or TensorFlow.
  • Proven track record of deploying large-scale LLM-backed services to production environments.
  • Extensive MLOps background, including CI/CD pipelines and model governance practices.
  • Expertise in cloud-native AI deployment on AWS or Azure with a focus on cost optimization.
  • Demonstrated commitment to responsible AI practices and operational excellence in regulated industries.
  • Strong leadership skills in mentoring senior engineers and setting engineering standards for agentic AI systems.

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