Role & responsibilities

Role Summary

We are seeking a highly skilled Generative AI & Conversational AI Expert to design, develop, and deploy
AIdriven 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.), RetrievalAugmented 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:
Develop AI-driven solutions using LLMs (GPT, LLaMA, Claude, etc.) for business applications.
Implement Retrieval-Augmented Generation (RAG) pipelines to provide AI with real-time
business knowledge.
Fine-tune and optimize LLMs for specific domains (e.g., Healthcare, Finance, Customer Support).
Work with vector databases (Pinecone, FAISS, Weaviate, ChromaDB) to store and retrieve AI-

relevant data.




Develop knowledge graphs to enhance AI reasoning and memory.
Conduct prompt engineering and prompt tuning to improve AI-generated responses.
Integrate LLM-based AI solutions into business automation workflows.

Preferred candidate profile

Required Skills & Qualifications:
3+ years of experience in AI/ML, NLP, or Conversational AI development.
Robust 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

Interested candidates can send their resume to [email protected]

Regards,

HR Manager

📌 AI Engineer (Telangana)
🏢 CAPTALENT HR
📍 Telangana