Java Sr Lead Software Engineer - OMS/Sales - VP

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors

• Develops secure and high-quality production code, and reviews and debugs code written by others

• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.

• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

• Drives decisions that influence the product design, application functionality, and technical operations and processes

• Serves as a function-wide subject matter expert in one or more areas of focus

• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle

   

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and advanced applied experience in Java

• Hands-on practical experience delivering system design, application development, testing, and operational stability

• Proficiency in back-end technologies notably Java, Springboot, High performance java, thread safety context , lockless approach and controlled object generation practices for high volume systems
• Demonstrated ability to independently solve design and functionality challenges with minimal supervision leveraging modern AI techniques.
• Experience working with cloud platforms such as AWS and Terraform based deliveries.
• Hands-on experience designing and building scalable applications using SQL and NoSQL databases.

• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.

• Ability to tackle design and functionality problems independently with little to no oversight
  Practical cloud native experience