Senior Lead Software Engineer, AI, Data, Cloud

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Plano, TX
Posted
10 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $200k
$170k most similar roles pay here $241k

This listing doesn't post a salary. Most similar roles pay $177,250–$223,750.

Based on 240 similar postings.

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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 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Senior Lead Software Engineer, AI, Data, Cloud

As a Senior Lead Software Engineer within Corporate Technology – Chief Technology Office, you will serve as a technical leader and individual contributor on an agile team focused on delivering secure, scalable technology products. You will contribute production code primarily in Python while owning end-to-end delivery from design through operations. Your core responsibilities include designing system architectures for machine learning workflows, developing agentic AI capabilities for workload optimization, and building reusable APIs and SDKs. You will manage infrastructure provisioning using Terraform and Infrastructure as Code on AWS containerized platforms like EKS or ECS. The role requires expertise in Databricks, LLM orchestration patterns, and Generative AI integration. You will also drive AI-assisted engineering practices to improve code quality while ensuring platform reliability through proactive monitoring and automated CI/CD pipelines for complex data and model serving systems.

What you'll do

  • Write production code primarily in Python and own the end-to-end delivery from design through operations.
  • Design and lead system architecture for components supporting end-to-end machine learning workflows.
  • Develop agentic AI capabilities to analyze workloads and generate optimization recommendations.
  • Build and maintain reusable APIs, SDKs, and reference implementations to ensure consistent platform adoption.
  • Automate infrastructure provisioning, configuration, and CI/CD pipelines using Infrastructure as Code.
  • Ensure platform reliability, scalability, and cost efficiency through proactive monitoring and incident response.
  • Drive the adoption of AI-assisted engineering practices to improve code quality and delivery speed.
  • Produce architecture and design artifacts that align with enterprise standards and best practices.

What we're looking for

  • Formal training or certification in software engineering concepts and 5+ years of applied experience.
  • Demonstrated experience in system design, application development, testing, and operational stability for distributed systems.
  • Strong hands-on depth in Python, including building/maintaining APIs and performing high-quality code reviews.
  • Experience delivering platforms involving Generative AI, LLM orchestration patterns, and agentic AI frameworks with production monitoring.
  • Experience with enterprise-authorized AI-assisted development tools and establishing validation standards for quality and security.
  • Practical experience with AWS, containerized platforms (EKS/ECS), and Terraform or equivalent Infrastructure as Code.
  • Required experience building and operating data and ML workloads on Databricks.
  • Comprehensive knowledge of the Software Development Life Cycle, agile delivery, CI/CD, and modern engineering quality controls.

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