Job Summary :

As a Generative AI Engineer, you will contribute to the development and deployment of AI-powered solutions using Large Language Models (LLMs) and cloud-based infrastructure. You will work closely with senior engineers to build, test, and integrate Retrieval-Augmented Generation (RAG) systems and AI applications that solve real-world business challenges.

Key Responsibilities :

- LLM Integration : Build and maintain LLM-based applications using industry-standard frameworks like LangChain, LlamaIndex, or Semantic Kernel.

- RAG Development : Implement and optimize RAG pipelines by managing data ingestion into vector databases such as Azure Cognitive Search, Pinecone, FAISS, or Weaviate.

- Tooling & Chatbots : Assist in developing AI-driven tools, including chatbots and copilots, using OpenAI, Azure OpenAI, or Hugging Face models.

- Backend Services : Develop and deploy GenAI microservices using FastAPI and Azure Functions.

- Prompt Engineering : Design and refine prompts to improve model output quality and consistency.

- Data Handling : Assist in preparing and processing datasets for model fine-tuning and retrieval tasks.

- Collaboration : Work within cross-functional teams to identify and operationalize new GenAI use cases for global clients.

Required Qualifications & Skills :

- Experience : 2-5 years in software engineering, with at least 1-2 years focused on AI/ML or LLM applications.

- Programming : Strong proficiency in Python and experience with RESTful API development.

- AI Frameworks : Familiarity with the GenAI ecosystem (e.g., Hugging Face, OpenAI API, LangChain).

- Data & Search : Basic understanding of vector embeddings, semantic search, and database management.

- Cloud Awareness : Experience or certification in Azure or similar cloud platforms is highly preferred.

- Education : Bachelor's degree in Computer Science, Data Science, or a related technical field.