Generative AI Engineer

Job Description :

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 modern 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.