Lead Software Developer - Python, AWS & AI Platform

Join JPMorganChase's Machine Learning Center of Excellence — where cutting-edge engineering meets real-world impact at global scale.

As a Lead Software Engineer at JPMorganChase within the Corporate Sector – Artificial Intelligence and Machine Learning Data Platforms and Machine Learning Center of Excellence team, you serve as a seasoned member of an agile team to design and deliver trusted, market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. You will collaborate with a multi-disciplinary community of experts focused exclusively on machine learning, working with cutting-edge techniques in disciplines such as deep learning and reinforcement learning.

Job responsibilities

• Design, develop, and maintain production-grade Python services and APIs that power high-impact machine learning platforms at enterprise scale

• Architect and implement high-throughput, low-latency distributed systems within Amazon Web Services (AWS) environments to support critical business workloads

• Build and manage scalable cloud-native applications leveraging AWS technologies including Elastic Kubernetes Service (EKS), Elastic Container Service (ECS), Managed Streaming for Apache Kafka (MSK), Simple Queue Service (SQS), and S3

• Develop reusable service frameworks, shared libraries, and modular application components that accelerate engineering delivery across teams

• Design and implement infrastructure-as-code solutions using Terraform and CloudFormation to enable repeatable, auditable, and scalable deployments

• Create and maintain monitoring, alerting, and observability solutions utilizing platforms such as Datadog, Dynatrace, and Splunk to ensure operational excellence

• Deploy and support applications in production environments while ensuring adherence to service-level objectives and service-level agreements

• Implement secure-by-design engineering practices, automated testing, and deployment strategies including blue/green and canary releases

• Review code, provide architectural guidance, and mentor engineers on software engineering best practices to elevate team capability

• Collaborate with product managers, platform engineering teams, and site reliability engineers to deliver scalable, business-aligned solutions

• Drive adoption of enterprise-approved AI-assisted engineering practices to improve code quality, operational excellence, troubleshooting, and delivery efficiency

Required qualifications, capabilities, and skills