Lead Software Engineer

JPMorgan Chase

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Quick summary

Work type: On-site
Location: Wilmington, DE
Employment: Full-time
Posted: 2 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

$161k most similar roles pay here $232k

This listing doesn't post a salary. Most similar roles pay $169,275–$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 1174 open roles on FindRole.

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At a glance

TL;DR · Lead Software Engineer

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As a Lead Software Engineer - Databricks/PySpark/AI within the Corporate Sector-Global Finance team, you will serve as a senior hands-on developer and technical leader in an agile environment. You will build, deliver, and optimize data products that power agentic AI systems capable of planning and executing multi-step tasks. Your daily responsibilities include developing data pipelines, retrieval and indexing layers, and tool-use infrastructure like APIs and function endpoints to connect agents with enterprise data. You will mentor junior engineers while ensuring high standards for code quality and security. The role requires expert-level Python and PySpark skills, along with extensive experience in Databricks, AWS (Glue, S3, Lambda), Spark, SQL, Snowflake, and Terraform. You will work with Lakehouse architecture, CI/CD pipelines, and LLM frameworks to solve complex problems involving autonomous agent orchestration and data management.

Skills

Python PySpark Databricks AWS Spark SQL Delta Lake Snowflake Terraform CI/CD LLMs RAG LangGraph AutoGen CrewAI Pinecone FAISS Chroma Agile

What you'll do

Build and optimize data pipelines to provide reliable, real-time access to structured and unstructured data for agentic AI systems.
Develop retrieval and indexing layers that enable AI agents to search and synthesize information across multiple sources.
Build tool-use infrastructure including APIs, data services, and function endpoints for AI agents to interact with enterprise systems.
Create orchestration and state management layers to support multi-step workflows, memory persistence, and task chaining.
Write production-quality Python and PySpark code while ensuring compliance with AWS best practices and CI/CD pipelines.
Implement and enforce data management standards regarding quality, security, and governance for AI-generated and consumed data.
Mentor junior and mid-level engineers through technical coaching, pair programming, and rigorous code reviews.
Drive the adoption of AI-assisted engineering practices to improve code quality and development speed across the team.

What we're looking for

Formal training or certification in software engineering concepts and 5+ years of applied experience.
Expert-level programming skills in Python and PySpark with a portfolio of production-grade code.
Extensive hands-on experience with Databricks, AWS ecosystem (Glue, S3, SQS/SNS, Lambda), Spark, and SQL.
Strong experience with Lakehouse/Delta Lake architecture, Snowflake, Terraform, LLMs, and data optimization techniques.
Experience building APIs, data services, retrieval systems, and infrastructure for agentic AI workflows.
Demonstrated experience leading the use of approved AI-assisted software development tools and ensuring secure, compliant adoption.
Extensive experience with CI/CD processes, automated testing frameworks, and agile methodologies.
Experience with agentic AI frameworks, vector databases, and RAG workflows (preferred).

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