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

JPMorgan Chase

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Jersey City, NJ
Posted: 23 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $202k

$187k most similar roles pay here $230k

This listing doesn't post a salary. Most similar roles pay $192,050–$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 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 · Lead Software Engineer, Python, AWS & Cloud-Native Services

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As a Lead Software Engineer – Python, AWS & Cloud-Native Services, you will join the Machine Learning Center of Excellence team to develop machine learning solutions for complex business problems involving deep learning and reinforcement learning. You will design and maintain production-grade Python services and APIs while architecting high-throughput, low-latency distributed systems in AWS environments. Your daily work involves building cloud-native applications using Amazon EKS, ECS, MSK, SQS, and S3, alongside implementing infrastructure-as-code via Terraform or CloudFormation. You will manage observability through Datadog, Dynatrace, and Splunk while ensuring secure-by-design practices and automated deployment strategies like canary releases. The role requires expertise in microservices architecture, CI/CD pipelines, and AI-assisted engineering tools to solve technical challenges within the firm’s data platforms and machine learning initiatives.

Skills

Python AWS Amazon EKS ECS Kafka SQS S3 Terraform CloudFormation Datadog Dynatrace Splunk CI/CD Microservices API Design Deep Learning Reinforcement Learning Generative AI LLM

What you'll do

Design, develop, and maintain production-grade Python services and APIs.
Architect and implement high-throughput, low-latency distributed systems in AWS environments.
Build and manage scalable cloud-native applications using EKS, ECS, MSK, SQS, and S3.
Implement infrastructure-as-code solutions using Terraform and CloudFormation.
Create and maintain monitoring, alerting, and observability solutions using Datadog, Dynatrace, and Splunk.
Deploy and support production applications while ensuring adherence to SLOs and SLAs.
Implement secure-by-design engineering practices, automated testing, and advanced deployment strategies.
Drive the adoption of AI-assisted engineering practices to improve code quality and delivery efficiency.

What we're looking for

Formal training or certification in software engineering concepts and 5+ years of applied experience.
Advanced proficiency in Python programming, object-oriented design, and modular software architecture.
Experience building and operating large-scale, high-performance cloud-native services within AWS environments.
Hands-on experience with AWS technologies including EKS, ECS, MSK (Kafka), SQS, and S3.
Strong experience implementing Infrastructure as Code (IaC) solutions using Terraform or CloudFormation.
Expertise in designing, deploying, and supporting distributed systems in production environments.
Experience with observability, monitoring, logging, and alerting platforms such as Datadog, Dynatrace, and Splunk.
Demonstrated experience utilizing approved AI-assisted software development tools for coding, testing, and troubleshooting.

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