Generative AI Engineer (5+yrs exp) (Indore)

We are seeking a highly skilled Generative AI Engineer with expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and scalable AI application development. The ideal candidate should have hands-on experience in designing, developing, and deploying enterprise-grade GenAI solutions using leading LLMs, modern AI frameworks, vector databases, and cloud platforms. You will collaborate with cross-functional teams to build intelligent AI applications that solve real-world business problems. Key Responsibilities - Design, develop, and deploy enterprise-grade Generative AI applications using LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, Llama, and similar models. - Build and implement Agentic AI workflows using frameworks like CrewAI, AutoGen, LangGraph, and LangChain Agents. - Design and optimize Retrieval-Augmented Generation (RAG) pipelines, embedding-based retrieval systems, and semantic search solutions. - Develop scalable AI services and APIs using Python, FastAPI, Flask, or similar frameworks. - Integrate LLMs with enterprise applications, third-party APIs, automation workflows, and business systems. - Implement advanced prompt engineering, hallucination reduction techniques, and model evaluation strategies to improve response quality. - Work with vector databases such as FAISS, Pinecone, Chroma, and Weaviate for efficient knowledge retrieval. - Deploy AI solutions on Azure, AWS, or GCP, ensuring scalability, security, and performance. - Monitor, evaluate, and optimize AI models for accuracy, latency, reliability, and cost efficiency. - Collaborate with Data Scientists, ML Engineers, Product Managers, and Software Developers to deliver production-ready AI solutions. - Follow software engineering best practices, including version control, CI/CD, Docker, and automated deployments. Required Skills & Qualifications - 4+ years of experience in Artificial Intelligence/Machine Learning, including model development, data preprocessing, exploratory data analysis (EDA), model training, and evaluation. - 2+ years of hands-on experience building Generative AI applications using LLMs, embeddings, RAG, and LLM-powered solutions. - Minimum 6 months of practical experience with Agentic AI frameworks such as CrewAI, AutoGen, LangGraph, or LangChain Agents. - Strong programming skills in Python. - Experience with ML libraries including Scikit-learn, Pandas, NumPy, and related AI/ML ecosystems. - Hands-on experience with OpenAI APIs, Azure OpenAI, Hugging Face, and prompt engineering techniques. - Experience developing RESTful APIs using FastAPI, Flask, or Django. - Strong understanding of REST APIs, microservices architecture, and system integration. - Experience with vector databases including FAISS, Pinecone, Chroma, or Weaviate. - Knowledge of cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP). - Familiarity with Git, Docker, CI/CD pipelines, and deployment best practices. - Solid analytical, problem-solving, and communication skills. Preferred Qualifications - Experience with LangSmith, MLflow, LlamaIndex, or similar LLM observability and evaluation tools. - Knowledge of AI governance, responsible AI practices, and LLM security. - Experience with Kubernetes, container orchestration, and scalable cloud-native deployments. - Exposure to MLOps pipelines and model monitoring solutions. - Relevant certifications in Azure AI, AWS AI/ML, or Google Cloud AI are a plus. Why Join Us - Work on cutting-edge Generative AI and Agentic AI technologies. - Build production-scale AI solutions for enterprise applications. - Collaborate with experienced AI, Data Engineering, and Product teams. - Opportunity to work with the latest LLMs, cloud platforms, and modern AI frameworks. - Continuous learning and career growth in one of the fastest-growing technology domains. Compensation: 50,000.00 - 90,000.00 per month Benefits - Health insurance - Provident Fund Application Question(s) - its a contract base job are you comfortable Language - English (Required) Location - Indore, Madhya Pradesh (Indore) (Required) Work Location: In person .