Software Engineer Intern

About the Educational Opportunity

PanMAS LLC is offering a structured, remote software engineering learning experience focused on technologies and development practices relevant to FinSeek AI. The program is designed for learning, mentorship, technical exploration, and exposure to the software product development lifecycle.

Learning Areas

The program may include:

• Software engineering fundamentals: Exploring application architecture, code organization, debugging approaches, and software development best practices.
• Frontend and backend technologies: Learning how application interfaces, backend services, and APIs work together.
• Databases and data modeling: Understanding database structures, data flows, and application integrations.
• AI-powered applications: Exploring how AI capabilities can be incorporated into software products.
• Product development lifecycle: Observing and learning about requirements gathering, technical planning, prototyping, testing, and code review.
• Development tools: Becoming familiar with version control, development environments, testing tools, and collaborative engineering workflows.

Mentorship and Learning Environment

Participants will have opportunities to:

• Receive technical guidance and feedback.
• Discuss engineering concepts and technical design decisions.
• Work through guided coding exercises and educational prototypes.
• Learn from demonstrations and supervised code reviews.
• Develop a better understanding of how engineering decisions relate to product design and user needs.
• Explore potential areas of technical specialization.

Who Should Apply?

This opportunity is suitable for students and aspiring developers who:

• Have an interest in software engineering or application development.
• Are familiar with at least one programming language, such as Python, JavaScript, TypeScript, or Java, or are actively learning one.
• Want to understand how modern software products are designed and developed.
• Are curious about databases, APIs, cloud technologies, or AI applications.
• Are receptive to mentorship, feedback, and collaborative learning.
• Can commit approximately 8–10 hours per week to agreed educational activities.

Prior professional experience is not required. Personal projects, coursework, and a willingness to learn are welcome.

Program Details

• Format: Fully remote.
• Time commitment: Approximately 8–10 hours per week.
• Compensation: Unpaid educational program.
• Duration: A defined term agreed upon before participation.
• Academic credit: May be available, subject to the student's institution.