Junior/Middle Backend Developer (Nodejs)

We are seeking a skilled Backend Developer to join our dynamic team focused on building a high-performance, scalable ERP and CRM management application powered by AI. You will collaborate closely with cross-functional teams, including backend, frontend, and AI engineers, to design and develop robust backend and frontend systems. Your role will involve integrating user data and ensuring the application delivers optimal performance and reliability.

Key Responsibilities:

• Develop and implement new features, resolve bugs, and propose initiatives to enhance product performance and infrastructure.
• Collaborate with cross-functional teams to define, design, and deliver innovative features.

Maintain the quality, responsiveness, and scalability of the applications.

Must-Have:

• Bachelor’s degree in Information Technology, Computer Science, or a related field.
• Minimum 2 years of professional experience in backend development using Node.js and NestJS.
• Strong experience designing and implementing RESTful APIs and working with SQL databases.
• Proficient in essential backend technologies such as Authentication, Authorization, Middleware, Queues, Cronjobs, and the Repository Pattern.
• Up-to-date knowledge of AI trends, with the ability to incorporate AI tools into development from a user-centric perspective.
• Excellent problem-solving abilities and time management skills, with a collaborative team mindset.
• Enthusiasm for learning new technologies and a product-focused approach.
• Positive attitude with an emphasis on innovation, continuous improvement, and openness to constructive feedback.
• Proficient in English for reading and writing technical documentation.

Nice-to-Have:

• Experience working with cloud platforms, especially Google Cloud Platform (GCP).
• Familiarity with containerization and orchestration tools such as Docker.
• Knowledge of Python or Golang for backend development.
• Experience with React.js, particularly in building Admin Dashboards.
• Exposure to LangChain and Retrieval-Augmented Generation (RAG) techniques.
• Proficiency in using Pinecone vector databases for data embedding.