Generative AI Engineer

Job description

**Job Description:** **Must Have Technical/Functional Skills** - **GenAI & LLM Frameworks** - **Vector Databases (e.g., AWS OpenSearch & Kendra, FAISS, Pinecone)** - **Word and Vector Embeddings (e.g., Word2Vec, BERT, Sentence Transformers)** - **Frameworks & Toolkits (AWS Bedrock, LangChain, LangGraph, LlamaIndex)** - **Cloud - AWS (preferably), Azure** - **Agentic AI & Automation - AWS Bedrock Agents, LangGraph, AutoGen, CrewAI** - **Programming & ML Skills** - **Python (mandatory), SQL (Postgres), NoSQL (Dynamo DB, Mongo DB), Graph DB (Neo4j,** **Neptune)** - **Libraries numpy, pandas, boto3, plotly, matplotlib, seaborn, ggplot, Scikit-learn,** **Requests, Beautiful Soup, NLTK)** - **ML algorithms (Supervised, Unsupervised and Ensemble) & Deep Learning (using** **frameworks like TensorFlow, PyTorch, etc.)** - **Web Development frameworks (Django, Flask, FastAPI)** - **Conversational AI** - **Chatbot development using LLMs or traditional NLP pipelines** - **UI development using Python Streamlit or Gradio libraries** **Roles & Responsibilities** **1. Design, develop, and fine-tune AI models using prompt engineering, fine-tuning, and retrieval-** **augmented generation (RAG).** **2. Implement and optimize large language model (LLM) workflows using LangChain, LangGraph, and** **LlamaIndex.** **3. Develop and orchestrate intelligent agents and agentic workflows for task automation.** **4. Integrate vector databases and embedding techniques (word/vector embeddings) for semantic** **search and knowledge retrieval.** **5. Build, test, and deploy chatbots and AI systems tailored to business requirements.** **6. Apply machine learning & Deep Learning models for classification, segmentation, and regression** **problems. 7. Integration with platforms and APIs 8. Collaborate with cross-functional teams to deliver production-grade AI applications.**