Lead Software Engineer, Python, AWS & Cloud-Native Services

JPMorgan Chase

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Quick summary

Work type
On-site
Location
Jersey City, NJ
Posted
3 days ago
Freshness
Confirmed live today

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How this pay compares to similar roles

Similar $190k
$163k most similar roles pay here $225k

This listing doesn't post a salary. Most similar roles pay $169,050–$211,200.

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 1138 open roles on FindRole.

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At a glance

TL;DR · Lead Software Engineer, Python, AWS & Cloud-Native Services

As a Senior Lead Software Engineer within the Corporate Artificial Intelligence and Machine Learning Data Platforms – Machine Learning Center of Excellence, you will design, build, and optimize high-performance, low-latency distributed systems. You will architect and implement Java Spring Boot-based services using object-oriented principles to create resilient, cloud-native solutions for machine learning and data infrastructure. Your daily work involves developing infrastructure-as-code via Terraform or CloudFormation, implementing observability with Datadog, Dynatrace, and Splunk, and managing containerized workloads using Docker and Kubernetes. You will leverage a suite of AWS services including MSK, SQS, S3, ECS, EKS, Lambda, Kinesis, RDS, DynamoDB, and Redshift. Additionally, you will lead technical design reviews, mentor engineers, and integrate AI-assisted engineering practices to ensure high availability and reliability for critical data processing systems across the enterprise.

What you'll do

  • Architect and implement high-performance, low-latency distributed services using Java Spring Boot.
  • Design resilient, cloud-native architectures utilizing a wide range of AWS managed services.
  • Develop and maintain infrastructure-as-code solutions using Terraform or CloudFormation for scalable deployments.
  • Implement and improve observability solutions including monitoring, alerting, and reporting across microservices.
  • Translate ambiguous requirements into stable service designs while communicating technical trade-offs to stakeholders.
  • Lead technical design reviews and establish engineering best practices for platform reliability and maintainability.
  • Own production outcomes by identifying and resolving performance bottlenecks and scalability constraints.
  • Drive the adoption of AI-assisted engineering practices to improve code quality and delivery speed.

What we're looking for

  • Formal training or certification in software engineering concepts and 5+ years of experience.
  • Very strong Java development skills using object-oriented principles and significant experience with Spring Boot.
  • Demonstrated experience designing and tuning low-latency processing for production distributed systems.
  • Hands-on experience with AWS services including MSK, SQS, S3, ECS, EKS, Lambda, Kinesis, RDS, DynamoDB, and Redshift.
  • Practical experience implementing monitoring and reporting solutions using Datadog, Dynatrace, and/or Splunk in production environments.
  • Proficiency in containerization and orchestration technologies including Docker and Kubernetes.
  • Experience with infrastructure-as-code tools like Terraform or CloudFormation (preferred).
  • Experience with CI/CD and modern delivery practices for scalable service delivery (preferred).

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