Senior Lead Software Engineer, AI Platform Engineer

JPMorgan Chase

Quick summary

Work type
On-site
Location
San Francisco, CAPalo Alto, CASeattle, WA
Salary
$171,000–$260,000 / yr
Posted
9 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $212k
This role $216k
$160k most similar roles pay here $271k

This role pays more than 51% of similar roles. Most pay $177,250–$246,150 — the shaded band above. At the midpoint, this role pays about $216k versus about $212k for comparable roles.

Based on 240 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.

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View all roles at JPMorgan Chase

At a glance

TL;DR · Senior Lead Software Engineer, AI Platform Engineer

As a Senior Lead Software Engineer on JPMorgan Chase’s Infrastructure Platforms team in the Corporate Sector, you will lead an agile team to develop and deploy secure, scalable cloud platforms optimized for AI/ML workloads. Your responsibilities include architecting infrastructure solutions that meet AI teams’ compute needs, monitoring and managing cloud resources for efficiency, and building CI/CD pipelines to streamline ML deployment. You will also champion firmwide SDLC frameworks and promote the use of AI-assisted engineering practices to enhance code quality and operational outcomes. The ideal candidate has hands-on experience with Kubernetes, Docker, Python or similar languages, and a deep understanding of cloud computing models and machine learning concepts. Additionally, proficiency in observability tools like Prometheus and Grafana, as well as familiarity with ML Ops tooling such as MLflow, is essential for this role that operates at the intersection of cutting-edge AI technology and enterprise-scale infrastructure challenges.

What you'll do

  • Design and deploy secure, scalable cloud platforms optimized for AI/ML workloads.
  • Translate compute needs from AI teams into detailed infrastructure requirements.
  • Build CI/CD pipelines and automation to streamline ML deployment and operations.
  • Monitor and optimize cloud resources for performance and cost efficiency.
  • Drive adoption of AI-assisted engineering practices to improve code quality and delivery speed.

What we're looking for

  • Extensive experience in system design and application development for secure, high-quality production code.
  • Proficiency with Kubernetes, Docker, and cloud computing models (IaaS, PaaS, SaaS).
  • Strong knowledge of machine learning concepts, including transformer architecture and ML training/inference.
  • Deep understanding of cloud component architecture and infrastructure as code practices.
  • Demonstrated leadership in using AI-assisted software development tools for coding, testing, and troubleshooting.
  • Expertise in responsible AI use, including data sensitivity and secure handling of inputs/outputs.

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