Sigmasoft - Generative AI Data Engineer

Role : Gen AI- Data Engineer

Key Responsibilities :

- Architect and implement generative AI and LLM-powered applications using frameworks such as LangChain, LangSmith, LlamaIndex, AutoGen, and Semantic Kernel.

- Build scalable cloud-based solutions using Microsoft Azure AI Services , integrating with AWS (Boto3) and Google Cloud (Vertex AI).

- Design and optimize vector search and database solutions using Chroma DB, FAISS, Pinecone, Qdrant, Milvus, and Cosmos DB to

enable efficient information retrieval.

- Apply AI techniques including Retrieval-Augmented Generation (RAG), embedding generation, prompt engineering, fine-tuning LLMs, and Agentic AI approaches.

- Perform document and image processing using Python-based tools such as PyPDF, PyOCR, and OpenCV.

- Develop APIs and web applications to deploy AI models using frameworks like FastAPI, Flask, Streamlit, or Gradio.

- Collaborate with cross-functional teams to integrate AI models with visualization tools such as Power BI and Tableau for business insights.

- Continuously monitor, troubleshoot, and improve AI workflows to ensure robustness, scalability, and security.

Skills :

- Proficient in Python programming, with experience in PyTorch, TensorFlow, and Hugging Face libraries.

- Hands-on experience with generative AI and LLM frameworks including LangChain, LangSmith, LlamaIndex, AutoGen, Semantic

Kernel.

- Skilled in cloud AI services such as Microsoft Azure AI Studio, Azure AI Search, Azure Cosmos DB, Azure Machine Learning, AWS

Boto3, and Google Cloud Vertex AI.

- Experience with vector databases and search technologies including Chroma DB, FAISS, Pinecone, Qdrant, Milvus, and Cosmos DB.

- Expertise in ETL pipeline design, data preprocessing, and managing multimodal workflows at scale.

- Knowledge of AI methodologies such as Retrieval-Augmented Generation (RAG), embedding techniques, prompt engineering, and

fine-tuning LLMs.

- Familiarity with document and image processing tools like PyPDF, PyOCR, and OpenCV.

- Ability to develop and deploy AI models through APIs and web frameworks such as FastAPI, Flask, Streamlit, or Gradio.

- Experience with data visualization tools like Power BI and Tableau is a plus.