JPMorgan Chase
Lead Software Engineer
Wilmington, DE +1 · Full-time · Posted Oct 22, 2026
- Location
- Wilmington, DE
Plano, TX - Experience
- 5+ years applied experience required. Preferred education alternatives specify 10+ years of applied experience with a bachelor's degree, or 5+ years with a master's degree.
- Education
- Formal training or certification on software engineering concepts. Preferred: bachelor's degree in computer science, Engineering, Mathematics, or a related quantitative field, or master's degree.
About the job
Leads development of cloud platform components and automation supporting the end-to-end machine-learning model lifecycle, including training, deployment, serving, and monitoring.
What you'll do
- Design, build, and maintain platform components and AWS infrastructure for model training and serving.
- Automate model deployment, testing, and releases, and monitor platform health and performance.
- Use enterprise-authorized AI coding tools to improve development while validating outputs for correctness, performance, and security.
What they ask for
- Formal training or certification in software engineering concepts and 5+ years of applied experience.
- Hands-on experience with enterprise-authorized AI-assisted software development tools, including evaluating and validating their outputs.
- Server-side development experience, including Web Services, XML, SOAP, REST, and JMS; experience building microservices with Spring Boot, Spring Core, MVC, Web Services, and Messaging.
- Experience with high-volume transactional systems, AWS services, RDBMS/SQL, and Agile development.
Nice to have
- MLOps and model-serving application experience; experience with AI and machine-learning development tools and frameworks.
- End-to-end project management experience; AWS Developer or Solution Architect Certification.
Tools
AWS, Databricks, EMR, ECS, S3, DynamoDB, EKS, RDS
AI focus
Uses enterprise-authorized AI coding assistants for coding, testing, troubleshooting, documentation, and automation; supports ML model lifecycle platforms and model serving. Requires responsible, secure use and validation of AI-generated outputs.
Model-written summary · the original posting is authoritative