Walk-in || Hexaware Drive_Data Scientist+ Gen AI_Hyderabad_27th June_Early Joiner

Job description

We have planned for Walkin Drive for Data Scientists on 27th June 2026 for Hyderabad Location. **We are looking for Immediate joiners only.Incase interested, please share profile on sanap@hexaware.com with below details:** **Name:** **Experience:** **Current CTC:** **Expected CTC:** **Notice Period:** **JD:** We are seeking a highly skilled AI/ML Engineer with strong expertise in Generative AI, Large Language Models (LLMs), and cloud platforms to join our team. The ideal candidate will be responsible for designing and developing intelligent automation solutions, specifically building AI agents to streamline and resolve support processes. You will work closely with cross-functional teams to build scalable, robust, and highly efficient AI-driven applications. **Key Responsibilities** - Design, develop, and deploy intelligent agents and GenAI solutions using advanced LLM frameworks. - Implement Retrieval-Augmented Generation (RAG) pipelines for accurate information retrieval and automated question-answering based on internal knowledge bases. - Process and structure large volumes of diverse documents to be ingested into vector databases. - Optimize and refine prompts (Prompt Engineering) to ensure accurate, context-aware, and safe responses from LLMs. - Build and maintain vector databases to support efficient similarity search and context retrieval. - Collaborate with software engineers, data scientists, and domain experts to integrate AI models into existing enterprise applications. - Evaluate and select appropriate LLMs (open-source or commercial) based on performance, cost, and latency requirements. **Skill Requirements** Must-Have Skills (Core Competencies) - **Programming:** Strong proficiency in Python with experience writing production-grade code. - **Generative AI & LLMs:** In-depth knowledge of Large Language Models and experience with frameworks like LangChain, LangGraph, LlamaIndex, or similar tools for building complex agentic workflows. - **RAG Architecture:** Proven experience designing and implementing Retrieval-Augmented Generation (RAG) systems. - **Cloud AI Platforms:** Hands-on experience working with LLMs on Google Cloud Platform (GCP) (e.g., Vertex AI, Gemini APIs). - **Vector Databases:** Strong understanding and practical experience with Vector Databases (e.g., Pinecone, Milvus, Qdrant, ChromaDB, or pgvector). - **Prompt Engineering:** Advanced prompt engineering skills with a focus on optimizing model outputs and handling edge cases. - **Document Processing:** Experience in parsing, chunking, and extracting information from various document formats (PDFs, HTML, Word) for ML pipelines.