Job description

Build and deliver scalable, production-grade data and cloud solutions for regulatory model applications and modernization initiatives at JPMorganChase. This hands-on individual contributor role focuses on engineering with PySpark/Python on Databricks (DBX) and AWS, partnering with cross-functional teams to design, implement, and support reliable systems; strong candidates may also bring experience enabling AI agent development. As a Lead Software Engineer (Individual Contributor) at JPMorganChase within Corporate & Enterprise Technology, you will build and deliver scalable data and cloud solutions for regulatory model applications and modernization initiatives. You’ll be hands-on across design, development, and production support, leveraging PySpark/Python, Databricks (DBX), and AWS, and collaborating closely with cross-functional partners. Job Responsibilities • Design, develop, and deploy regulatory model applications and cloud modernization solutions. • Build scalable distributed data processing solutions using PySpark/Python and Databricks (DBX). • Implement secure, resilient AWS-based architectures and integration patterns. • Write high-quality code, tests, and documentation; contribute to reviews and release readiness. • Communicate architecture and delivery plans through clear technical documentation and tech decks. • Partner with product, data, model, and platform teams to deliver outcomes on time. Required qualifications, skills, and capabilities • 5+ years of software engineering experience and strong CS fundamentals • Strong hands-on experience with PySpark, Python, Databricks (DBX), and AWS. • Experience building and operating production-grade systems (quality, reliability, observability). • Strong communication skills; ability to work in dynamic, ambiguous environments. Preferred Qualifications, Capabilities, and Skills • C++, Scala, and/or Java experience. • Data engineering experience; ML exposure is a plus. • Strong candidates: experience enabling or building AI agent development (LLM-enabled workflows/orchestration, evaluation/guardrails). • Advanced degree in Computer Science or related field. Shape technology strategy and drive impactful projects in a dynamic environment using C++, PySpark/Scala, AWS

Requirements

Must-haves

Design, develop, and deploy regulatory model applications and cloud modernization solutions.
Build scalable distributed data processing solutions using PySpark/Python and Databricks (DBX).
Implement secure, resilient AWS-based architectures and integration patterns.
Write high-quality code, tests, and documentation; contribute to reviews and release readiness.
Communicate architecture and delivery plans through clear technical documentation and tech decks.
Partner with product, data, model, and platform teams to deliver outcomes on time.
Required qualifications, skills, and capabilities
5+ years of software engineering experience and strong CS fundamentals
Strong hands-on experience with PySpark, Python, Databricks (DBX), and AWS.
Experience building and operating production-grade systems (quality, reliability, observability).
Strong communication skills; ability to work in dynamic, ambiguous environments.
C++, Scala, and/or Java experience.
Strong candidates: experience enabling or building AI agent development (LLM-enabled workflows/orchestration, evaluation/guardrails).
Advanced degree in Computer Science or related field.
Shape technology strategy and drive impactful projects in a dynamic environment using C++, PySpark/Scala, AWS

Nice-to-haves

Preferred Qualifications, Capabilities, and Skills
Data engineering experience; ML exposure is a plus.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonawsaijavamlllm

Platform: oracle-cloud
Effort: medium