Experience : 4Yrs - 10 Yrs

• Build GenAI applications using Python for tasks like summarization, chatbots and intelligent automation.
• Fine tune and deploy LLMs and traditional ML models for classification, prediction, and decisioning.
• Design solutions using embeddings, vector search, and retrieval augmented generation (RAG).
• Integrate models with AWS services like SageMaker, Lambda, Bedrock and data platforms like Snowflake.
• Collaborate across teams to embed AI/ML into business workflows and automation pipelines.

Preferred Skills

• Strong Python skills with experience in GenAI frameworks like LangChain, Hugging Face, OpenAI.
• Solid grounding in ML algorithms, model training and evaluation.
• Familiarity with prompt engineering, tokenization and model optimization.
• Hands-on with AWS tools for scalable deployment and serverless execution.
• Ability to connect models to APIs, data sources and orchestration tools.
• Build GenAI applications using Python for tasks like chatbots, summarization and intelligent automation.




• Develop and fine tune LLMs and ML models for classification, prediction, and decision support.
• Design solutions using embeddings, vector search, and retrieval augmented generation (RAG).
• Deploy models using Azure Machine Learning and Azure OpenAI scale with Azure Functions and Cognitive Services.
• Integrate AI systems with APIs, enterprise data platforms and business workflows.

Preferred Skills

• Solid Python development with experience in GenAI frameworks like LangChain, Hugging Face, OpenAI.
• Solid foundation in ML algorithms, training pipelines and evaluation techniques.
• Familiarity with prompt engineering, tokenization and model optimization.
• Hands-on with Azure cloud tools for model lifecycle, deployment,and serverless execution.
• Ability to connect models to data sources, automation tools and orchestration platforms.

📌 Lead-Data Insight (Hyderabad)
🏢 Cognizant
📍 Hyderabad