Live opening · Posted 1 day ago

Java Software Engineer

Mphasis · Mumbai, Maharashtra, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 1 day ago
CompanyMphasis
LocationMumbai, Maharashtra, India (On-site)
SalaryUp to 3.5M INR/yr
Work modeNo
SkillsJava, Spring Boot, AWS, Docker, Kubernetes, Terraform
SourceLinkedin
ListedPosted 1 day ago

About the role

Description supplied by the original job listing.

Job Summary
We are looking for an experienced Java Developer with strong expertise in Java, AWS, Kubernetes, DevOps, and AI technologies. The candidate should have hands-on experience developing scalable applications, building microservices, deploying cloud-native solutions, and implementing CI/CD pipelines.
Key Responsibilities
Design, develop, and maintain backend applications using Core Java and Spring Boot.
Build scalable microservices and RESTful APIs.
Deploy, manage, and optimize applications on AWS.
Containerize applications using Docker and manage deployments using Kubernetes.
Implement and maintain CI/CD pipelines and DevOps automation.
Monitor application performance, troubleshoot issues, and improve system reliability.
Integrate AI/GenAI capabilities into applications or leverage AI-powered development tools.
Collaborate with development, QA, and DevOps teams to deliver high-quality software.
Participate in code reviews, technical design discussions, and Agile ceremonies.
Required Skills
8–10 years of overall software development experience.
Strong hands-on experience in Java, Spring Boot, and Microservices.
Practical experience with AWS cloud services.
Hands-on experience with Kubernetes and Docker.
Strong understanding of DevOps, CI/CD pipelines, and deployment automation.
Good knowledge of REST APIs, distributed systems, and databases.
Exposure to AI/GenAI technologies or AI-assisted development tools.
Strong problem-solving and communication skills.
Good to Have
Experience with Terraform or CloudFormation.
Knowledge of monitoring and observability tools.
Exposure to LLM integration, prompt engineering, or RAG.
Experience with cloud-native architecture and production support.

Work arrangement
No

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