Senior Java & Node.js Backend Developer (8+ Years)

MindBrain · India

Job Description – Senior Java & Node.js Backend Developer

Experience: 8–10 Years

Location: Remote

Notice Period: Immediate Joiners Preferred

Asset Collection: Mumbai / Chennai / Bangalore / Gurgaon

Position Overview

We are looking for an experienced Senior Java & Node.js Backend Developer with 8–10 years of strong hands-on experience in backend application development, microservices architecture, API development, event-driven systems, and cloud technologies.

The ideal candidate should have strong expertise in Java, Spring Boot, Node.js, Microservices, Kafka, PostgreSQL, SQL Server, AWS, Docker, OpenShift, Jenkins, and API security . Experience with communication platforms such as Email and SMS is an added advantage.

The candidate should also demonstrate practical experience using AI-assisted development tools such as GitHub Copilot and Claude Code Assist , along with an understanding of responsible AI usage, privacy, code provenance, prompting practices, and development guardrails.

Key Responsibilities

• Design, develop, maintain, and enhance highly scalable backend services and microservices using Java 8–21, Spring Boot, and Node.js v16/v22 .
• Design and implement secure, scalable, and high-performance REST APIs , including API gateway management using Apigee .
• Develop and manage event-driven and asynchronous architectures using Apache Kafka, AWS MSK, or equivalent messaging platforms.
• Design, optimize, and maintain database objects, queries, stored procedures, and performance-critical operations using PostgreSQL and SQL Server .
• Manage and enhance existing Email and SMS middleware platforms , including support, development, troubleshooting, and performance optimization.
• Work with communication platforms such as SparkPost, Twilio, Syniverse , or equivalent technologies.
• Build and maintain containerized applications using Docker and deploy/manage workloads on OpenShift / ROSA .
• Maintain and enhance CI/CD pipelines using Jenkins and Git.
• Monitor application health, performance, availability, and logs using New Relic and ELK Stack .
• Implement appropriate authentication, authorization, API security, and other security best practices.
• Collaborate with internal application teams, vendors, architects, business stakeholders, and other technical teams.
• Troubleshoot production issues, perform root-cause analysis, and drive performance and reliability improvements.
• Contribute to technical design, architecture discussions, code reviews, and engineering best practices.
• Use AI-assisted development tools effectively while following organizational policies related to privacy, security, prompt patterns, code provenance, limitations, and governance .
• Provide technical support and guidance to team members and contribute to a collaborative engineering environment.

Required Technical Skills

Must-Have Keywords:

• Java 8–21
• Spring Boot
• Microservices
• Node.js v16/v22
• Apache Kafka / AWS MSK
• PostgreSQL
• SQL Server
• REST APIs
• Apigee
• Docker
• OpenShift / ROSA
• Jenkins
• Git
• New Relic
• ELK Stack
• HTML5
• CSS
• JavaScript
• AWS
• AI-Assisted Development Tools – Claude Code Assist / GitHub Copilot

Good to Have

• Experience with SparkPost, Twilio, Syniverse , or similar Email/SMS communication platforms.
• Experience working on high-volume messaging and communication middleware platforms.
• Strong understanding of cloud-native application development and AWS services.
• Experience with production support, application performance optimization, and troubleshooting.
• Knowledge of secure software development practices and API governance.

AI-Assisted Development Experience

Candidates should have demonstrated experience incorporating AI-assisted development tools into their daily engineering workflows, including:

• GitHub Copilot, Claude Code Assist, or equivalent AI coding assistants.
• Effective prompt patterns for software development and troubleshooting.
• Understanding of AI-generated code limitations and validation requirements.
• Awareness of privacy, security, governance, and code-provenance considerations.
• Ability to review, test, validate, and appropriately govern AI-generated code.