Senior Research Fellow - Full Stack AI Developer

• Design, develop, test, and maintain full-stack components (front-end and back-end) for a decision-support dashboard.
• Translate decision-tree logic and AI-driven models into interactive web and mobile applications.
• Integrate multiple data sources including weather APIs, forecast data, historical data, and agricultural knowledge repositories.
• Implement visualization modules to analyze data variability and advisory effectiveness.
• Develop WhatsApp bot capabilities and multilingual messaging frameworks for advisory dissemination.
• Coordinate closely with climate scientists, agronomists, and AI experts to ensure coherent integration between scientific models and digital implementation.
• Provide technical documentation, debugging support, and manage deployment workflows on cloud platforms.
• Assist with training and onboarding for users and internal stakeholders.

• Master’s degree in computer science,AL/ML, information technology, software engineering, or a related field.
• Minimum 1-2 years of experience in full-stack development, especially for decision support systems or AI-applications.
• Proven skills with:
• Backend frameworks: Django, Django REST Framework; familiarity with Flask or Node.js is a plus.
• Frontend technologies: HTML, CSS (Bootstrap 4), JavaScript (jQuery); modern JS frameworks like React, Angular, or Vue are desirable.
• Databases: MySQL, Apache Druid (with PyDruid), and preferably PostgreSQL or MongoDB.
• API development via REST (GraphQL is a plus).
• Python and JavaScript (TypeScript is a bonus).
• Web application deployment tools like Gunicorn, NGINX, or Apache Tomcat.
• Dashboard/presentation libraries (e.g., Highcharts) and interactive visualization techniques.
• Cloud experience (AWS, Azure, GCP) and deployment tools (Docker, Kubernetes) are advantageous.
• Basic interest or understanding of AI/ML workflows like LLMs, RAG, or agentic architectures for automation is desirable.
  

Required:

Key Stack: Django / REST, JS frameworks, MySQL / Druid, Python, Docker, Cloud

AI Components: LLMs, Retrieval-Augmented Generation (RAG), agentic automation

Collaboration: Interdisciplinary teamwork with climate scientists and agronomists