Software Engineer/Senior Software Engineer - AI/ ML

Position : Software Engineer/Senior Software Engineer AI/ML Department: Engineering &; Technology | Function: AI/ML Platform Engineering Min Exp- 3 to 7 yrs salary u to 12 lpa Preferred Qualifications: Experience with agentic AI architectures for task orchestration. Familiarity with AIOps, AI-driven decision-making, automation strategies, knowledge graphs and structured data extraction Background in Healthcare AI, Financial AI, Enterprise AI solutions, contact center AI, or process automation. Role Summary We are seeking a highly skilled Generative AI & Conversational AI Expert to design, develop, and deploy AI-driven solutions that enhance automation, improve user experiences, and enable intelligent decision- making. This role will focus on both Conversational AI (chatbots, voice assistants, Natural Language Processing (NLP), and Conversational AI frameworks) and Generative AI (LLMs, RAG, prompt engineering, and AI-based content generation). The ideal candidate should have expertise in LLMs (GPT, LLaMA, Claude, Mistral, etc.), Retrieval- Augmented Generation (RAG), Knowledge Graphs, NLP, and AI model fine-tuning, AWS Lex, OpenAI, Rasa, Dialogflow, or similar platforms. They will also be responsible for building AI-powered assistants, integrating AI into business workflows, and optimizing AI models for real-world applications. Responsibilities Generative AI (Gen AI) Responsibilities Conversational AI Responsibilities Required Skills &; Qualifications: 3-7 years of experience in AI/ML, NLP, or Conversational AI development. Strong AI & NLP Expertise Hands-on experience with LLMs, Transformer models, OpenAI, Hugging Face, LangChain. Proficiency in AI Frameworks Experience with TensorFlow, PyTorch, Rasa, AWS Lex, Dialogflow. Vector Databases & RAG Knowledge of Pinecone, FAISS, Weaviate, ChromaDB for AI memory storage. Conversational AI Development – Experience building intelligent chatbots & voice assistants. Understanding of speech-to-text (STT), text-to-speech (TTS), and multi-modal AI interactions. Model Fine-Tuning & Optimization – Hands-on with LLM training, prompt tuning, and hyperparameter tuning. API & Backend Integration – Experience integrating AI into enterprise applications, RPA tools, and cloud services. Cloud & Deployment – Experience with AWS, Azure, GCP, Docker, Kubernetes for AI model deployment. Knowledge Graphs & Data Processing – Ability to structure data for AI reasoning. Hands-on experience with APIs, webhooks, and AI model integrations. Experience in cloud-based AI deployments (AWS, Azure, GCP). Proficiency in Python, Node.js or Java Strong problem-solving and analytical skills. Willingness to learn new technology stack and scale up• Please apply to this job here, we will call you once your profile is shortlisted.