Lead Software Engineer - Java/AWS

Job Responsibilities

• Works with different stakeholders to review business requirements, architecture and design.
• Involves in coding, pair programming and code reviews.
• Writes unit tests and software automation.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support).
• Establishes consistent validation standards (secure coding, peer review, automated testing) and promotes reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Supports Integration, UAT, and Performance testing.
• Releases software on UAT and production; Participate in production support and application monitoring.

Required Qualifications, Capabilities, And Skills

• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Hands-on practical experience in system design, application development, testing, and operational stability.
• Experience in developing web-based applications using J2EE technology.
• Experience using Spring framework for building enterprise java applications.
• Experience in developing Rest APIs.
• Experience in using Oracle, Cassandra databases.
• Experience using BlazeMeter, Splunk, Dynatrace.
• Experience in manual testing using Postman/SoapUI.
• Experience using Swagger tool to create the API specifications.
• Experience in using Agile Scrum methodology for tracking the team work.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices.

Preferred Qualifications, Capabilities, And Skills

• Exposure to AWS cloud technologies.
• Experience in using Kafka for data streaming.
• AWS or Cloud certifications.
• Experience in Temporal Durable Execution technology.
• Experience writing automation tests using Cucumber framework.
• Cloud Foundry experience for developing and managing the web application.
• Understanding best practices for CI/CD, Applicant Resiliency, and Security.