Artificial Intelligence Engineer- Pan India

Job description

Job Summary We are seeking a highly skilled **Generative AI Engineer** with strong expertise in **Python, Machine Learning, Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Natural Language Processing (NLP), and Cloud Technologies**. The ideal candidate will design, develop, and deploy scalable AI-powered applications leveraging modern AI frameworks, vector databases, cloud platforms, and microservices architecture. Key Responsibilities Generative AI & LLM Development - Design and implement AI-powered applications using **Large Language Models (GPT, Llama, Claude, Gemini, Mistral, etc.)**. - Build and optimize **Retrieval Augmented Generation (RAG)** pipelines for enterprise use cases. - Develop conversational AI solutions, chatbots, virtual assistants, and AI agents. - Create and optimize prompts using advanced **Prompt Engineering** techniques. - Fine-tune, evaluate, and deploy LLMs for business-specific requirements. - Integrate AI solutions with enterprise applications and APIs. Machine Learning & NLP - Develop, train, and deploy Machine Learning models using Python-based frameworks. - Implement NLP solutions including: - Text Classification - Named Entity Recognition (NER) - Sentiment Analysis - Information Extraction - Document Processing - Semantic Search - Perform model monitoring, evaluation, and performance optimization. RAG & Vector Databases - Build scalable RAG architectures using LangChain and related frameworks. - Implement embedding generation and semantic search solutions. - Work with vector databases such as: - Pinecone - ChromaDB - Weaviate - FAISS - Milvus - Azure AI Search - Optimize retrieval accuracy, latency, and relevance. Backend Development - Develop scalable backend services using: - Python - Java - Spring Boot - Build and maintain RESTful APIs and microservices. - Design robust integration layers between AI models and enterprise systems. Cloud & DevOps - Deploy AI and ML workloads on: - AWS - Azure - Develop serverless applications using **Azure Functions**. - Containerize applications using **Docker**. - Implement CI/CD pipelines and cloud-native deployment strategies. - Monitor and optimize cloud infrastructure costs and performance. Database Management - Design and optimize SQL queries and database schemas. - Work with relational databases and AI data pipelines. - Manage metadata and vector storage solutions. Required Skills Technical Skills - Strong programming experience in **Python**. - Good experience in **Java** and **Spring Boot**. - Strong understanding of **Machine Learning** and **Deep Learning** concepts. - Hands-on experience with **Large Language Models (LLMs)**. - Experience building production-grade **RAG** solutions. - Expertise in **Natural Language Processing (NLP)**. - Experience with **LangChain**, LangGraph, LlamaIndex, or equivalent frameworks. - Knowledge of **Prompt Engineering** techniques. - Experience with **Vector Databases** and Embedding Models. - Strong SQL and database design skills. - Experience developing **REST APIs** and **Microservices**. - Hands-on experience with **Docker**. - Experience with **AWS** and/or **Microsoft Azure**. - Experience with **Azure Functions**. Preferred Skills - Experience with MLOps tools and model deployment. - Knowledge of Kubernetes. - Familiarity with Hugging Face ecosystem. - Experience with AI Agents and Agentic AI frameworks. - Knowledge of Generative AI governance and responsible AI practices. - Exposure to multi-modal AI applications. Qualifications - Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Engineering, or related field. - Experience delivering enterprise-scale AI applications.