Generative AI Engineer

:

We are looking for a skilled Generative AI Engineer with hands-on experience in developing and deploying AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and up-to-date AI frameworks.

Key Responsibilities :

- Design, develop, and deploy Generative AI applications using LLMs and foundation models.
- Build RAG pipelines using embeddings, vector databases, and semantic search.
- Implement prompt engineering, AI agents, and LLM-based workflows.
- Develop and integrate AI solutions using frameworks such as LangChain, LangGraph, or LlamaIndex.
- Build APIs and backend services using Python and integrate AI models with enterprise applications.
- Evaluate model performance, optimize response accuracy, and reduce hallucinations and inference costs.
- Deploy and monitor AI applications on cloud platforms such as AWS, Azure, or GCP.
- Implement security, data privacy, and responsible AI practices.

Required Skills :

- Strong programming skills in Python.




- Hands-on experience with Generative AI and LLMs.
- Practical experience in RAG, embeddings, and vector databases.
- Knowledge of prompt engineering and LLM orchestration frameworks.
- Experience with REST APIs and backend development.
- Understanding of AI model evaluation, deployment, and performance optimization.
- Familiarity with cloud platforms and Git-based development workflows.

Preferred Skills :

- Experience with AI agents and tool calling.
- Knowledge of Docker, Kubernetes, CI/CD, and MLOps.
- Exposure to cloud AI services such as Azure OpenAI, Amazon Bedrock, or Google Vertex AI.

Interview Process :

- First Round : Berribot AI interview, which can be completed at the candidate's convenience.
- Final Round : Face-to-face interview.

Candidates are requested to share their earliest preferred date and time for the first-round interview.

📌 Coforge - Generative AI Engineer - LLM/RAG (India)
🏢 Coforge
📍 India