GEN A.I

� apply genai to accelerate software development (e.g. code generation test automation documentation). � design and implement business use cases using genai (e.g. intelligent assistants content generation knowledge retrieval). � collaborate with cross-functional teams to build and refine scalable genai solutions. � expertise in prompt engineering: ability to craft optimize and iterate prompts for diverse tasks like summarization classification extraction and multi-turn conversations. familiarity with techniques like chain-of-thought zero/few-shot prompting and guardrails. � rag (retrieval-augmented generation) implementation skills: experience in designing and deploying rag pipelines using vector databases (e.g. faiss weaviate pinecone) to ground llm outputs in enterprise data. � working knowledge of genai mlops and deployment: understanding of ci/cd pipelines for ai/llm models model versioning monitoring and governance. familiarity with platforms like mlflow azure ml aws sagemaker or custom deployment frameworks for scalable genai apps.