Lead Software Engineer - .net and React

JPMorgan Chase JPMorgan Chase · Banking · Bengaluru, Karnataka, India · Commercial & Investment Bank

Lead Software Engineer role focused on developing and deploying scalable full-stack applications using .NET and React, with a strong emphasis on cloud-native solutions on AWS and Infrastructure as Code using Terraform. The role also involves driving team adoption of AI-assisted engineering practices for code quality, delivery speed, and operational outcomes, ensuring validation standards and promoting reuse.

What you'd actually do

  1. Designs, develop, test, and deploy scalable full-stack applications using .NET and React
  2. Builds and maintain RESTful APIs and backend services using C# and ASP.NET Core
  3. Develops responsive, user-friendly front-end interfaces using React, TypeScript, HTML, and CSS
  4. Implements cloud-native solutions on AWS (compute, storage, networking, monitoring, security)
  5. Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.

Skills

Required

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Hands-on experience in full-stack application development and system design
  • Strong proficiency in C#, .NET, and ASP.NET Core
  • Strong front-end experience with React (with TypeScript). Practical experience with AWS services and cloud deployment patterns
  • Hands-on Terraform experience for Infrastructure as Code. Experience with relational and/or NoSQL databases and query optimization
  • Strong debugging, testing, and performance tuning skills
  • Understanding of SDLC, secure coding, and agile development practices
  • Familiarity with CI/CD, application resiliency, and observability best practices
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

Nice to have

  • Experience with containerization and orchestration (Docker, Kubernetes, ECS/EKS)
  • Knowledge of microservices and event-driven architecture
  • Familiarity with automated testing frameworks and test strategy
  • Experience with monitoring/logging tools (CloudWatch, ELK, Datadog, etc.). Exposure to enterprise-scale distributed systems

What the JD emphasized

  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices