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Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards contributes learnings and reusable patterns to improve broader team effectiveness.
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.
Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations ability to guide peers on safe and effective usage within team practices.
Experience with latest DevOps practices and tools
Job ID: 152423765
Skills:
Java, Software Development Life Cycle, Machine Learning, Cloud, Artificial Intelligence, Continuous Delivery, Agile Methodologies, Automation, AWS, AI-assisted Software Development Tools, Mobile
Skills:
react.js , Postgressql, Sql, AWS ECS, Spring Boot, Aws Ec2, Emr, Java, Aws S3, Aws Lambda, Cloud Formation, Kafka, AWS, Oracle, Sqs, AWS EKS, Terraform, Athena, EventBridge, Security, Application Resiliency, AWS KMS
Skills:
Java, Prometheus, Kafka, Grafana, Datadog, Spring, Nosql, Devops, RDBMS, Dynatrace, Dbms, AI-assisted software development tools