Infrastructure Engineer

We are seeking a Software Engineer to join the Software Development Life Cycle (SDLC) infrastructure team responsible for the end-to-end developer environment of a large-scale platform. The SDLC team builds and maintains the IDE experience, CI/CD pipelines, testing frameworks, deployment tools, and provides front-line developer support. This role emphasizes building tools that streamline development workflows, enable automation, enhance productivity, and accelerate delivery using technologies like Scala, Python, and Java.

The team’s vision is Straight Through Processing (STP)—minimizing manual intervention in the development cycle to only necessary human steps like code reviews and analysis. As part of this initiative, we are also exploring how AI can enhance automation, data aggregation, and pattern recognition to further improve the development lifecycle. Job Responsibilities: Design, develop, and maintain infrastructure to support developer workflows, from coding to deployment Build and maintain CI/CD pipelines and testing/deployment systems Debug complex issues in build and test infrastructure to identify root causes Collaborate across teams to implement best practices in software delivery automation Continuously improve developer productivity through tooling, automation, and observability enhancements Support IDE integrations and developer environment configurations Contribute to the use of AI and data-driven tools to further optimize development cycles Create clear documentation and user-friendly UX for internal tooling Required Skills: Bachelor's degree in Computer Science, Information Technology, Engineering, or related field 3+ years of software development experience in Agile/DevOps environments Proficiency in Java, Python, or Scala Experience with Build Automation tools such as Gradle or Ant Experience with IDEs like IntelliJ Strong understanding of Git/Bitbucket, branching models, and merge conflict resolution Hands-on experience with CI/CD tools like Jenkins, TeamCity Strong problem-solving and analytical thinking skills Familiarity with Agile methodologies including Scrum and Kanban Strong written and verbal communication skills Ability to work in a fast-paced, collaborative environment Preferred Skills: Experience with Groovy scripting Exposure to containerization tools (Docker) Experience with cloud platforms (AWS, Azure) Understanding of system architecture and application infrastructure Interest in leveraging AI/ML to automate engineering workflows Certifications: Not mandatory, but relevant cloud or DevOps certifications are a plus Education: Bachelor's degree in computer science, Engineering, or related field (or equivalent experience) Email ID * This field is required Please enter valid emailId.

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