Mern Stack Backend Developer Intern (In Office)

Job description

Waygood is a fast-growing EdTech company focused on building high-impact digital platforms powered by modern web technologies, scalable backend systems, and AI-driven solutions. We aim to solve real-world problems through performance-focused engineering, automation, and innovation.

About the Role

We are looking for a highly motivated Backend-Focused MERN Stack Intern who is passionate about backend engineering, databases, system performance, and AI integrations. This role is ideal for candidates who want to gain hands-on experience building scalable applications, optimizing backend systems, and working with modern technologies used in production environments.

Key Responsibilities

• Develop and maintain RESTful APIs using Node.js and Express.js
• Design scalable, modular, and maintainable backend architectures
• Implement authentication and authorization mechanisms (JWT, OAuth)
• Follow best practices for code quality, security, and performance

Database Management

• Work extensively with MongoDB and Mongoose
• Build and optimize complex database queries
• Utilize MongoDB Aggregation Framework ($lookup, $group, $project, etc.)
• Improve database efficiency through indexing and query optimization

Performance Optimization

• Implement caching strategies using Redis or in-memory caching
• Optimize API response times and overall system performance
• Handle large datasets and improve application scalability
• Monitor and troubleshoot backend bottlenecks

AI & API Integrations

• Integrate AI-powered APIs such as OpenAI and other machine learning services
• Build automation workflows and intelligent backend features
• Develop recommendation engines, content generation systems, and AI-driven functionalities

System Integration

• Collaborate with frontend developers using React.js and Next.js
• Integrate third-party APIs, payment gateways, and external services
• Ensure seamless communication between frontend and backend systems

Testing & Debugging

• Identify, troubleshoot, and resolve backend issues
• Write clean, scalable, and maintainable code
• Participate in code reviews and technical discussions

Required SkillsMust Have

• Strong knowledge of JavaScript (ES6+)
• Experience with Node.js, Express.js, and MongoDB
• Understanding of RESTful APIs and asynchronous programming
• Knowledge of MVC architecture and backend development principles
• Strong problem-solving and analytical skills

Good to Have

• Experience with MongoDB Aggregation Framework
• Knowledge of Redis or caching mechanisms
• Basic understanding of system design concepts
• Familiarity with Git, GitHub, and Postman

Bonus Skills

• Experience working with AI APIs (OpenAI or similar platforms)
• Basic knowledge of React.js or Next.js
• Familiarity with Docker, cloud platforms, or deployment workflows

Internship Structure

• 1–2 weeks of training followed by 2–3 months of internship
• All successful candidates who complete the training period will be eligible for the internship program
• Selected interns will receive a stipend for both the training period and the internship duration, subject to successful completion of training

Ideal Candidate Profile

• Passionate about backend development and system architecture
• Curious and eager to learn emerging technologies
• Interested in AI-powered applications and automation
• Comfortable working with databases and performance optimization
• Strong ownership mindset and attention to detail
• Ability to work independently as well as within a collaborative team

What You Will Gain

• Hands-on experience building scalable backend systems
• Exposure to production-level application architecture
• Practical experience with database optimization and performance engineering
• Experience integrating AI-powered solutions into real products
• Mentorship from experienced developers and engineers
• Opportunity to contribute to impactful live projects
• Certificate of Completion
• Performance-based incentives
• Opportunity for a Pre-Placement Offer (PPO) or Full-Time