Python-GenAI-LLMOps

Technical Requirements: • Primary skills:Technology->Data Science->Machine Learning,Technology->Geographical Information System->Spatial Databases->SQL Server,Technology->Machine Learning->Python Responsibilities: Key Responsibilities Develop and deploy Generative AI applications using LLMs (GPT, Llama, etc.) Build and maintain LLM pipelines, including prompt engineering and fine-tuning Design and implement end-to-end AI/ML workflows (data → model → deployment) Work with vector databases for semantic search and retrieval (RAG architecture) Implement LLMOps practices for monitoring, evaluation, and versioning Integrate LLMs into applications via APIs and microservices Optimize model performance, cost, and latency Collaborate with data engineers, product teams, and stakeholders Conduct testing, validation, and debugging of AI models Ensure security, compliance, and responsible AI practices Required Skills & Qualifications Technical Skills Strong proficiency in Python Hands-on experience with Generative AI & LLM frameworks: OpenAI / Azure OpenAI APIs Hugging Face Transformers LangChain / LlamaIndex Experience with prompt engineering and RAG (Retrieval-Augmented Generation) Familiarity with vector databases (FAISS, Pinecone, Weaviate, Chroma) Knowledge of ML/DL frameworks (PyTorch / TensorFlow – basics) Experience in API development (FastAPI, Flask) Understanding of RESTful services and microservices architecture Preferred Skills: Technology->AI-Data science->Machine Learning,Technology->AI-Data science->PYTHON,Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag)