Job Description
<p><p><b>Role : Gen AI- Data Engineer</b><br/><br/><b>Key Responsibilities : </b></p><p><br/></p><p>- Architect and implement generative AI and LLM-powered applications using frameworks such as LangChain, LangSmith, LlamaIndex, AutoGen, and Semantic Kernel.<br/><br/></p><p>- Build scalable cloud-based solutions using Microsoft Azure AI Services , integrating with AWS (Boto3) and Google Cloud (Vertex AI).<br/><br/></p><p>- Design and optimize vector search and database solutions using Chroma DB, FAISS, Pinecone, Qdrant, Milvus, and Cosmos DB to </p><p>enable efficient information retrieval.<br/><br/></p><p>- Apply AI techniques including Retrieval-Augmented Generation (RAG), embedding generation, prompt engineering, fine-tuning LLMs, and Agentic AI approaches.<br/><br/></p><p>- Perform document and image processing using Python-based tools such as PyPDF, PyOCR, and OpenCV.<br/><br/></p><p>- Develop APIs and web applications to deploy AI models using frameworks like FastAPI, Flask, Streamlit, or Gradio.<br/><br/></p><p>- Collaborate with cross-functional teams to integrate AI models with visualization tools such as Power BI and Tableau for business insights.<br/><br/></p><p>- Continuously monitor, troubleshoot, and improve AI workflows to ensure robustness, scalability, and security.<br/><br/><b>Skills : </b></p><p><br/></p><p>- Proficient in Python programming, with experience in PyTorch, TensorFlow, and Hugging Face libraries.<br/><br/></p><p>- Hands-on experience with generative AI and LLM frameworks including LangChain, LangSmith, LlamaIndex, AutoGen, Semantic </p><p>Kernel.<br/><br/></p><p>- Skilled in cloud AI services such as Microsoft Azure AI Studio, Azure AI Search, Azure Cosmos DB, Azure Machine Learning, AWS </p><p>Boto3, and Google Cloud Vertex AI.<br/><br/></p><p>- Experience with vector databases and search technologies including Chroma DB, FAISS, Pinecone, Qdrant, Milvus, and Cosmos DB.<br/><br/></p><p>- Expertise in ETL pipeline design, data preprocessing, and managing multimodal workflows at scale.<br/><br/></p><p>- Knowledge of AI methodologies such as Retrieval-Augmented Generation (RAG), embedding techniques, prompt engineering, and </p><p>fine-tuning LLMs.<br/><br/></p><p>- Familiarity with document and image processing tools like PyPDF, PyOCR, and OpenCV.<br/><br/></p><p>- Ability to develop and deploy AI models through APIs and web frameworks such as FastAPI, Flask, Streamlit, or Gradio.<br/><br/></p><p>- Experience with data visualization tools like Power BI and Tableau is a plus.</p><br/></p> (ref:hirist.tech)