Full Stack Engineer

Job Description:

Develops IT Solutions under guidance. Leverage Agile and DevOps practices to build IT solutions, making extensive use of AI-assisted development throughout the SDLC. They are learning to understand the business value their IT Solutions deliver. They develop on multiple development platforms (i.e. MS Azure, AWS, Salesforce, Web). They contribute to building AI-powered solutions and AI agents as a core part of their work — either for AI platform capabilities or for global digital products. They work in small Development Teams and take ownership of items in the Sprint Backlog. They look for opportunities to create more efficient DevOps processes leveraging automation and new (ARB approved) tools together with DevOps Engineers. They work hand-in-hand with Operations Engineers to improve flow between Development and Operations to deliver value faster.


Skills:

Artificial Intelligence (AI); Generative AI; Software Engineering Practices; AI Platforms; AI Architecture; Software Quality Assurance (SQA); Software Engineering; DevOps; Product Management


Qualification:

  • - Exposure to or hands-on experience developing AI-powered applications and building AI agents (e.g. LLM integration, function/tool calling, RAG). A strong interest and demonstrated ability to learn in this area is essential.
  • - Proficient with AI coding tools (e.g. GitHub Copilot, Claude Code, Cursor) as a daily part of the development workflow.
  • - Working experience in Java. Knowledge of Python, JavaScript or Go is a plus (Python preferred for AI development).
  • - Bachelor's degree or above, majored in software engineering, computer science, information technology or related area. 1-3 years of software development experience, or strong internship/project experience.
  • Willingness to learn and the ability to work as part of a team.
  • Basic understanding of micro service design and development. Exposure to Spring Framework SpringBoot/SpringCloud or Dubbo is a plus.
  • Basic knowledge in SQL and/or NoSQL database. Such as MySQL, PostgreSQL, Redis, Elasticsearch, Mongo DB are preferred.
  • Good command of English.

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