Working with amazing people and awesome products not only makes your work meaningful, it drives you to make our world a better place. Great ideas have a way of becoming great products, services and customer experiences very quickly at Apple. The Infrastructure Software Development team is looking for a passionate, self-motivated and hard-working engineer to be part of a diverse, fast paced and high-energy team. Bring passion and dedication to your job and there's no telling what you could accomplish.
Description
We are currently seeking a highly motivated Infrastructure Software Engineer. The ideal candidate should possess a strong background in Java Spring Boot backend development and React JS frontend development, combined with experience leveraging AI-assisted development tools and LLMs to enhance engineering workflows. They should be passionate about creating modern, intelligent, user-friendly applications. In addition to technical expertise, excellent communication and interpersonal skills are crucial. The ideal candidate should be able to collaborate effectively with business partners from diverse backgrounds and varying technical expertise levels.
Minimum Qualifications
- Bachelor’s degree in Computer Science, Software Engineering or a related field or equivalent practical experience.
- Proficiency in React JS and related frontend technologies like HTML,CSS, Tailwind including experience with Redux and React Router.
- Experience in Java Spring boot based API development using JSON API spec.
- Hands-on experience with Hibernate.
- Experience in NoSQL databases like MongoDB.
- Knowledge of containerization (Docker, Kubernetes) and CI/CD tools.
- Familiarity with Claude skills, prompt engineering, MCP or similar agent orchestration patterns.
Preferred Qualifications
- Experience working in Data Center Infrastructure Management domain.
- Experience in building, configuring and leveraging AI agents, Claude skills and LLM-powered capabilities to automate routine tasks, streamline workflows and enhance developer productivity.
- Understanding of responsible AI practices, including output validation and human-in-the-loop design patterns.
- Excellent analytical and problem-solving skills.
- Results-oriented and demonstrates ownership and accountability.
- Communicate clearly and collaborate with other team members.
