Adds to team culture of diversity, opportunity, inclusion, and respect
Adds to team culture of opportunity, inclusion, and respect
Evolve and apply AI in software development and 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), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting 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.
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), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting 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.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Experience in the Software Development Life Cycle, including hands-on development experience
Hands-on experience in Java/J2EE, REST Services, Spring Boot
Strong experience writing complex SQL queries, joins, PL/SQL, functions, and stored procedures.
Hands-on experience in public cloud – Kubernetes, AWS and extensive experience with ECS, S3, RDS, Lambda, CloudWatch, Eventbridge, and Step Functions, as well as infrastructure automation using Terraform
Proficiency in designing and implementing RESTful APIs for enterprise-scale applications.
Ability to design software systems using object-oriented principles and practices.
Experience in building Decoupled Systems.
Proficiency in using design patterns and technologies to decouple system components, enhancing flexibility and maintainability.
Proficiency in unit testing frameworks such as JUnit and Mockito for ensuring code quality.
Knowledge of messaging platforms such as Apache Kafka
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
Familiarity with modern front-end technologies like React JS, JavaScript, typescript
Experience with SQL performance tuning, JDBC, and ORM frameworks (Hibernate/JPA)
Familiarity with DevOps practices, containerization and orchestration
Exposure to AI systems such as Copilot, Claude
