About the Role :

We are looking for a GenAI Engineer with 2+ years of relevant experience to join the technology team of a leading organisation in the education and learning domain. The role is suited for an AI/ML professional with hands-on experience in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI and modern AI application development.

Key Responsibilities :

- Design and develop Generative AI applications using Large Language Models and modern AI technologies.

- Build and integrate LLM-powered applications for practical business and user-facing use cases.

- Develop and maintain Retrieval-Augmented Generation (RAG) pipelines.

- Work with document processing, chunking, embeddings, retrieval and contextual response generation.

- Implement solutions using vector databases and semantic search.

- Work with Agentic AI and Multi-Agent architectures to build intelligent workflows and task-oriented AI applications.

- Use frameworks such as LangGraph, Google ADK or similar Agentic AI frameworks.

- Integrate LLM APIs and open-source models into applications and enterprise systems.

- Experiment with different models, prompts and AI architectures to improve application quality and performance.

- Work with Python for AI application development and integration.

- Contribute to the deployment and maintenance of AI applications in production environments.

- Implement appropriate monitoring, logging, testing and observability for GenAI applications.

- Collaborate with engineering teams to integrate AI capabilities into existing products and platforms.

- Work with cloud platforms such as AWS, GCP or Azure for deploying and scaling AI solutions.

Required Skills:

- 2+ years of relevant experience in Artificial Intelligence, Machine Learning, Generative AI or related areas.

- Strong hands-on programming experience with Python.

- Practical experience working with Generative AI and Large Language Models (LLMs).

- Hands-on experience building or integrating RAG-based applications.

- Understanding of LLM application architecture and prompt engineering.

- Experience with embeddings, vector databases and semantic search.

- Understanding of Agentic AI and Multi-Agent systems.

- Experience with at least one cloud platform - AWS, GCP or Azure.