Lead Software Engineer, Data & AI Platform Engineer

JPMorgan Chase

Confirmed live 2 days ago Trusted

Quick summary

Work type: On-site
Location: Jersey City, NJ
Posted: 16 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $208k

$187k most similar roles pay here $230k

This listing doesn't post a salary. Most similar roles pay $192,050–$223,750.

Based on 240 similar postings.

Employer

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.

Most-posted roles

View all roles at JPMorgan Chase

At a glance

TL;DR · Lead Software Engineer, Data & AI Platform Engineer

Role Posting Log in to save

Lead Software Engineer - Data & AI Platform Engineer joins the Commercial & Investment Banking's Payments Technology team to build a Data & AI Platform for analytics and automation. This role involves designing and implementing scalable data pipelines, ETL/ELT workflows, and platform components including data cataloging, quality frameworks, and semantic layers. The engineer will lead an Agentic AI initiative to automate platform engineering and develop the Agentic Autonomous Lakehouse capability. Key responsibilities include developing production-grade code, performing technical troubleshooting, and leading communities of practice. Required skills include Python, Java, SQL, Spark, Flink, Kafka, Airflow, and Databricks. The role requires expertise in data modeling, Kubernetes, and cloud services like AWS S3 or Redshift. Additionally, the candidate must possess experience with LLMs, RAG architectures, vector databases, and infrastructure as code using Terraform.

Skills

Python Java SQL Spark Flink Airflow Kafka Databricks AWS S3 Glue Redshift Athena EMR Kubernetes Docker Terraform CI/CD LLMs RAG Vector Databases dbt Iceberg

What you'll do

Design and maintain scalable batch and real-time data pipelines using Spark, Airflow, Kafka, and Flink.
Develop data platform components including cataloging, quality frameworks, and semantic layers with embedded governance.
Implement data modeling strategies such as fact/dimensional models to support analytics and reporting.
Lead the Agentic AI initiative to automate platform engineering, architecture, and self-service pipeline provisioning.
Translate business requirements from product and analytics teams into production-grade technical solutions.
Write, review, and debug high-quality production code while ensuring system stability and security.
Evaluate external vendors and internal technologies to determine architectural fit for existing systems.
Lead communities of practice to drive the adoption of emerging software engineering technologies.

What we're looking for

Formal training or certification in software engineering concepts.
5+ years of applied experience in software engineering or data platform development.
Advanced proficiency in Python, Java, and SQL.
Hands-on experience with distributed processing frameworks like Apache Spark and Flink.
Experience designing and operating data pipelines on Databricks using Airflow.
Proficiency with cloud data services such as AWS S3, Glue, Redshift, Athena, EMR, or Lake Formation.
Experience engineering production-grade platforms on Kubernetes with open catalog integrations like Iceberg or Unity Catalog.
Experience developing Agentic AI, LLMs, RAG architectures, and vector databases.

Save