Principal Software Engineer

JPMorgan Chase JPMorgan Chase · Banking · Hyderabad, Telangana, India · Consumer & Community Banking

Principal Software Engineer at JPMorgan Chase focused on designing, developing, and maintaining complex, scalable Java frameworks using Spring Boot, with a significant emphasis on integrating AI solutions, including RAG and Applied AI, into enterprise systems. The role involves hands-on coding, architectural design, leading best practices, and providing technical thought leadership in AI.

What you'd actually do

  1. Design, develop, and maintain complex, scalable, and reusable Java frameworks using Spring Boot, ensuring they meet industry standards for reliability, efficiency, and performance.
  2. Lead the creation and adoption of coding patterns and best practices across the organization’s development community, driving standardization and consistency.
  3. Architect and implement robust, secure, and high-performance frameworks for both cloud and on-premises environments, leveraging cloud-native services (e.g., AWS).
  4. Collaborate with cross-functional teams to define integration strategies and technical solutions aligned with business goals.
  5. Provide technical thought leadership, staying abreast of industry trends, emerging technologies, and best practices to guide the team and organization.

Skills

Required

  • Java (Core Java & EE)
  • Spring Boot
  • Spring frameworks (Spring MVC, Spring Cloud, Spring GraphQL, Spring Security, Spring AI)
  • Microservices development
  • Cloud-native development (AWS)
  • Performance tuning
  • Relational database skills
  • SQL
  • Data modeling
  • High availability database architectures
  • Streaming technologies (Kafka, RabbitMQ)
  • CI/CD pipelines
  • DevOps practices
  • Unit and integration testing
  • Test-driven development
  • Strategic thinking
  • Technical strategy development
  • Communication skills
  • Presenting technical concepts to senior leaders

Nice to have

  • API design and development
  • Enterprise-grade API solutions
  • High availability development and architectural practices
  • AI Engineering
  • Retrieval-Augmented Generation (RAG)
  • Applied AI
  • Integrating AI solutions into enterprise frameworks
  • Agile development processes (SCRUM/KANBAN)
  • JIRA
  • GitHub/Bitbucket
  • Jenkins
  • Maven/Artifactory
  • System design
  • Application development
  • Testing
  • Operational stability

What the JD emphasized

  • Deep expertise in Java (Core Java & EE), Spring Boot, and related Spring frameworks (Spring MVC, Spring Cloud, Spring GraphQL, Spring Security, Spring AI).
  • Proven experience building performant, scalable, and reliable microservices and frameworks for both cloud (AWS) and on-premises deployments.
  • Demonstrated technical thought leadership in AI, guiding teams on best practices for AI integration, staying abreast of emerging trends, and driving the adoption of innovative technologies.

Other signals

  • Spring AI
  • Applied AI
  • integrating AI solutions into enterprise frameworks
  • Retrieval-Augmented Generation (RAG)