Zensar Technologies—GenAI Developer

Job description

Description: Key Responsibilities - Design, develop, and deploy enterprise Generative AI applications using Azure OpenAI Services. - Build Retrieval-Augmented Generation (RAG) pipelines using embeddings and vector databases. - Develop scalable REST APIs using FastAPI and Flask. - Integrate Vision LLMs for image, document, and multimodal understanding. - Build document processing pipelines using PyMuPDF for PDF extraction, parsing, and preprocessing. - Implement semantic search using FAISS Vector Database. - Engineer prompts and optimize LLM responses for enterprise use cases. - Develop AI-powered chatbots, document Q&A, summarization, and intelligent automation solutions. - Optimize AI models for latency, scalability, and cost efficiency. - Integrate AI solutions with enterprise applications and cloud services. - Implement monitoring, evaluation, and experimentation frameworks using Opik or similar LLM observability tools. - Collaborate with product managers, architects, data scientists, and software engineers to deliver AI solutions. - Ensure AI applications follow security, governance, and responsible AI best practices. Required Skills Generative AI - Large Language Models (LLMs) - Prompt Engineering - Retrieval-Augmented Generation (RAG) - Embeddings - Semantic Search - AI Agents - Function Calling - Context Management - Model Evaluation Cloud & AI Platforms - Azure OpenAI Service - Azure AI Services - Azure Cognitive Search (preferred) - Azure Storage - Azure Functions (preferred) Programming - Python (Advanced) - FastAPI - Flask - REST API Development - Async Programming AI Frameworks & Libraries - LangChain - LlamaIndex - PyMuPDF - FAISS Vector Database - Vision LLMs - OpenAI SDK - Transformers (preferred) Development Tools - Visual Studio Code (VS Code) - PyCharm - Git - GitHub/Azure DevOps - Docker Observability & Evaluation - Opik - Prompt evaluation - LLM monitoring - Experiment tracking - Performance benchmarking Required Experience - 5–10 years of software development experience with strong Python expertise. - Minimum 2–4 years of hands-on experience in Generative AI and LLM-based application development. - Experience implementing enterprise RAG architectures. - Strong experience with Azure OpenAI. - Experience integrating Vision LLMs for document and image processing. - Hands-on experience with vector databases such as FAISS. - Experience building production-ready AI APIs using FastAPI or Flask. - Experience processing large PDF/document repositories using PyMuPDF. - Experience with AI evaluation and observability tools such as Opik. - Experience deploying AI applications in cloud environments. Nice-to-Have Skills - LangGraph - AutoGen/CrewAI - Azure AI Search - Cosmos DB - PostgreSQL - Redis - Kubernetes - MLflow - Hugging Face - OCR (Azure Document Intelligence, Tesseract) - CI/CD pipelines - MLOps