Lead Software Engineer Python

JPMorgan Chase

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: Houston, TX
Employment: Full-time
Posted: 13 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 $181k

$133k most similar roles pay here $229k

This listing doesn't post a salary. Most similar roles pay $146,775–$214,250.

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 1018 open roles on FindRole.

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At a glance

TL;DR · Lead Software Engineer Python

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As a Lead Software Engineer-PYTHON within the Enterprise Technology, Consumer & Community Banking risk technology team, you will serve as a core technical contributor in an agile environment. You will design, code, and deliver automation solutions, including LLMs and agents, to eliminate manual work and streamline remediation for security vulnerabilities and infrastructure findings. Your daily responsibilities involve governing application risk, ensuring secure coding practices, and driving the adoption of AI-assisted engineering tools to improve code quality and delivery speed. You will manage production services by implementing monitoring, logging, and anomaly detection while maintaining site reliability standards. The role requires advanced proficiency in Python or Java, experience with Big Data and ETL pipelines using Hortonworks or AWS, and expertise in SRE practices using tools like Grafana, Dynatrace, Prometheus, Datadog, and Splunk to ensure scalable, secure systems.

Skills

Java Python AWS Kubernetes Docker CI/CD SRE Prometheus Grafana Datadog Splunk Dynatrace Big Data ETL Infrastructure as Code LLMs Hortonworks

What you'll do

Design, code, and deliver automation solutions including LLMs to eliminate manual operational work and streamline workflows.
Govern application risk, controls, and compliance by ensuring adherence to firm standards and managing remediation of findings.
Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
Manage security and data accountability by ensuring robust authentication, vulnerability hygiene, and compliant data storage.
Coordinate across product and engineering teams to prioritize execution and align large developer communities on key workstreams.
Operate resilient production services by implementing monitoring, logging, anomaly detection, and site reliability engineering practices.
Mentor and coach engineers on the responsible use of AI tools while ensuring security and performance standards.

What we're looking for

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Proven track record designing, coding, testing, and delivering production-grade software in at least one technology stack.
Advanced development experience in Java or Python with excellent debugging and troubleshooting skills for complex production issues.
Experience building scalable data processing, Big Data, and ETL pipelines using Hortonworks or AWS-based solutions.
Working knowledge of core infrastructure including routers, load balancers, compute, storage, networks, and cloud products.
Proficiency in SRE practices, observability tools (Grafana, Dynatrace, Prometheus, Datadog, Splunk), and enterprise architecture.
Demonstrated ability to lead the responsible use of AI-assisted engineering tools while ensuring security and data integrity.
Current AWS credential or recognized automation/DevOps credentials (preferred); hands-on experience with Docker and Kubernetes (preferred).

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