Lead Software Engineer, Java, AWS, AI/ML

JPMorgan Chase

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: Jersey City, NJ
Employment: Full-time
Posted: 70 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $190k

$140k $234k

below market most similar roles pay here above market

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 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, Java, AWS, AI/ML

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As a Lead Software Engineer within the Corporate technology - Instrument Reference Data team, you will serve as a seasoned member of an agile team designing and delivering trusted, scalable technology products. You will execute creative software solutions, develop secure production code, and lead the adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed. Your daily work involves designing and delivering scalable ML systems for batch and real-time inference, including data pipelines, model training, and monitoring. You will utilize Java, Spring boot, Kafka, Hibernate, and AWS for cloud-native solutions. Key responsibilities include managing SQL/NoSQL data volumes, implementing CI/CD, and ensuring secure coding practices. You will also lead communities of practice for MLOps, LLM patterns, and feature stores to solve complex architectural problems.

Skills

Java Spring Boot Kafka AWS SQL NoSQL Hibernate ECS micro-services CI/CD Infrastructure-as-Code MLOps LLM RAG Agile Secure Coding Feature Stores Observability

What you'll do

Develop secure, high-quality production code and perform code reviews and debugging for other team members.
Design and deliver scalable ML systems including data pipelines, model training, deployment, and performance monitoring.
Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
Identify and automate the remediation of recurring issues to improve the operational stability of software and ML systems.
Lead evaluation sessions with external vendors and internal teams to assess architectural designs and technical credentials.
Lead communities of practice to promote the use of leading-edge technologies like MLOps and LLM patterns.
Apply SDLC toolchain knowledge to improve automation value and establish consistent validation standards for secure coding.

What we're looking for

Formal training or certification on software engineering concepts and 5+ years of applied experience.
Hands-on practical experience delivering system design, application development, testing, and operational stability.
Experience with micro-services architecture, design patterns, and technologies including Java, Spring boot, Kafka, and Hibernate.
Experience building cloud-native solutions on AWS and deploying containerized services like ECS.
Experience processing large data volumes and performing data analysis using SQL/NoSQL.
Experience with CI/CD, infrastructure-as-code, automation, authentication, secrets management, encryption, and secure coding practices.
Experience in Agile methodologies and leading the use of approved AI-assisted software development tools.
Preferred AWS Certification.
Preferred experience building AI/GenAI services (RAG, agent/tool orchestration, evaluation frameworks, guardrails) in production.
Preferred experience with event-driven architecture, streaming, and data processing patterns for high-volume systems.