Drimva

JPMorgan Chase

Lead Software Engineer (Java/Spring and Python) - Data Protection & Recovery

OH · Full-time · Posted Jul 28, 2026

Experience
5+ years applied experience; 8+ years of experience with Java.
Education
Formal training or certification on software engineering concepts.

About the job

Leads architecture and delivery of resilient Java and Python services for data protection and recovery, including observability, secure development, disaster recovery, and AI-enabled automation of enterprise SAP processes.

What you'll do

  • Provide technical leadership, own Java service architecture, and develop secure production code while mentoring engineers.
  • Drive resilience, observability, disaster recovery, secure SDLC, and CI/CD practices; support incidents and on-call operations.
  • Build agentic AI capabilities to automate complex actions in enterprise SAP processes.

What they ask for

  • Formal training or certification in software engineering concepts and 5+ years of applied experience; 8+ years of experience with expert-level Java proficiency.
  • Strong experience with Spring Boot, microservices, event-driven API design, and expert-level Python microservices development.
  • Hands-on expertise in resiliency engineering and disaster recovery, secure SDLC, observability, and Kafka or other messaging platforms.
  • Experience with approved AI-assisted development tools, CI/CD and Git, containers and orchestration, infrastructure as code, and AWS; strong technical communication and mentoring skills.

Nice to have

  • Experience with service mesh, API gateways, and contract governance at scale.
  • Familiarity with frontend technologies, additional programming languages, engineering standards across teams, or UNIX/Linux and shell scripting.

Tools

Java, Spring Boot, Python, Kafka, Git, AWS, SAST/DAST, SAP

AI focus

Use approved AI-assisted development tools for coding, code review, test acceleration, and troubleshooting; build agentic AI capabilities to automate complex enterprise SAP processes; promote safe, compliant use and validation of AI outputs.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 4, 2026 (UTC)