Engineering Productivity Lead - DevOps Lead / Platform Engineer

Role & responsibilities

• 10+ years of experience in Software Engineering, DevOps, Platform Engineering, or Developer Experience (DevEx).
• Strong hands-on experience with Java, Tomcat, JSP, Servlets, and legacy Java monolithic applications.
• Deep understanding of Git workflows, branching strategies, pull request management, and code review best practices.
• Experience designing and maintaining CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or similar tools.
• Strong knowledge of test automation, unit testing, integration testing, dependency mocking, and service virtualization.
• Experience working with OpenAPI/Swagger, REST APIs, and API contract-driven development.
• Good understanding of SQL databases and managing database dependencies in development and testing environments.
• Proficiency in Bash, Python, or similar scripting languages for automation and developer tooling.
• Experience building internal engineering platforms, developer tools, or productivity frameworks is highly preferred.
• Familiarity with containerization and modern development practices using Docker and related technologies is an advantage.
• Exposure to AI-powered developer tools such as Codex, Claude Code, or GitHub Copilot, with the ability to integrate them into engineering workflows.
• Strong problem-solving, stakeholder management, and cross-functional collaboration skills.
• Excellent communication skills with the ability to influence engineering teams and drive process improvements.

Preferred candidate profile

We are looking for a technology leader who is passionate about improving the developer experience rather than only managing infrastructure. The ideal candidate has a strong software engineering background, understands legacy Java ecosystems, and enjoys building tools, automation, and workflows that enable engineering teams to deliver high-quality software faster. They should have a continuous improvement mindset, be hands-on with modern DevOps practices, and actively drive AI-assisted development and engineering excellence across the organization.