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.
Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
Applies technical troubleshooting to break down solutions and solve technical problems of basic complexity
Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems
Required qualifications, capabilities, and skills
Bachelor Degree in Computer Science/ Information systems/ Engineering or related disciplines
Minimum 5 years of Software development hands on experience
Hands-on practical experience in system design, application development, testing, and operational stability
Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
Demonstrable ability to code in one or more languages
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 across the whole Software Development Life Cycle
Exposure to agile methodologies such as CI/CD, Applicant Resiliency, and Security
Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Preferred qualifications, capabilities, and skills
Familiarity with modern front-end technologies
Exposure to cloud technologies
Blockchain knowledge is preferred but not a requirement