Software Engineering Apprentice, USA
LUNARTECH
United StatesFresher1h agovia LinkedIn
About the Role
The Software Engineering Apprentice role is a part-time, remote position designed for individuals who want hands-on experience building AI-native software systems.
Key Responsibilities
- Assist in the development of backend and frontend components.
- Write clean and maintainable code.
- Contribute to the integration of AI models and data pipelines.
- Debug issues and run tests.
- Document features.
- Collaborate with experienced engineers and data professionals in agile workflows.
- Learn and apply best practices in software engineering, version control, code reviews, and deployment processes across experimental and production environments.
- Participate in knowledge-sharing sessions.
- Receive mentorship.
- Support project teams delivering AI solutions for real-world clients.
Requirements & Tech Stack
- Foundational skills in Software Development and Programming.
- Experience in at least one modern language (e.g., Java, Python, or similar).
- Basic knowledge of Databases, including designing tables, writing queries, and understanding data models.
- Familiarity with Linux, command-line tools, and general system administration concepts relevant to development environments.
- Introductory to intermediate skills in Java, including object-oriented programming, debugging, and working with libraries or frameworks.
- Experience with Git or other version control systems.
- Understanding of software testing and documentation practices.
Qualifications
- Strong problem-solving abilities.
- Attention to detail.
- Willingness to learn in a fast-paced, AI-focused environment.
- Ability to work independently in a remote setting.
- Communicate clearly in written and spoken English.
- Collaborate across time zones.
- Current enrollment in or completion of a degree, bootcamp, or structured program in computer science, software engineering, data science, or a related field is beneficial, but not strictly required.
- Interest in AI, machine learning, or data-intensive applications.