About the Role
We are looking for a highly skilled GenAI Engineer to design, develop, and optimize large-scale AI solutions leveraging LLMs, Retrieval-Augmented Generation (RAG), NLP, and advanced analytics techniques. The ideal candidate will have solid expertise in building intelligent AI applications, designing robust evaluation frameworks, and deploying scalable data processing pipelines using Python, PySpark, and SQL.
Key Responsibilities
Retrieval-Augmented Generation (RAG) & NLP
Design and implement advanced RAG pipelines using vector databases, semantic search, and knowledge retrieval frameworks.
Develop and optimize NLP models for text processing, classification, summarization, information extraction, and conversational AI use cases.
Build intelligent retrieval systems leveraging embeddings, chunking strategies, reranking techniques, and contextual search.
Work with vector databases such as Pinecone, Weaviate, Chroma, FAISS, or Elasticsearch.
Prompt Engineering & Agentic AI
Develop and optimize sophisticated prompting techniques for improved LLM performance.
Implement function calling, tool usage, chain-of-thought workflows, and structured outputs to enable deterministic AI agent behavior.
Design and evaluate multi-agent and agentic AI frameworks.
Create guardrails, validation mechanisms, and monitoring frameworks for production-grade AI systems.
Statistical Modeling & Evaluation
Apply statistical methods and hypothesis testing to assess model performance and reliability.
Design evaluation frameworks using quantitative metrics to measure accuracy, relevance, hallucination rates, and user experience.
Build predictive models and data-driven approaches to enhance AI solution quality.
Conduct A/B testing and experiment design to optimize model performance.
Data Analysis & Feature Engineering
Perform exploratory data analysis (EDA) on structured and unstructured datasets.
Develop feature engineering and data synthesis techniques to improve training and evaluat
📌 Generative AI Engineer (Gurugram)
🏢 EXL
📍 Gurugram