01Overview
Generative AI Engineer (35 Years Experience)We are seeking a Generative AI Engineer to design and implement AI-driven solutions that automate document processing, decision support, and analytical workflows. The role will focus on building LLM-powered applications using Retrieval-Augmented Generation (RAG) to deliver accurate, explainable, and domain-aware outputs from large, complex datasets.
Key ResponsibilitiesDesign, build, and deployRAG-based AI solutionsusing large language models for document analysis, summarization, and intelligent automation.Develop and optimizeretrieval pipelinesleveraging embeddings and vector databases.Implement prompt engineering strategies and context-aware generation workflows.Integrate LLM applications into production systems via APIs and microservices.Collaborate with data engineering teams to prepare structured and unstructured data for retrieval and indexing.Evaluate model outputs for accuracy, relevance, and hallucination reduction.Monitor AI pipelines and continuously improve system performance.Ensure responsible AI usage, data privacy, and compliance with regulatory requirements.Required Skills & Experience35 years of experience in AI/ML, NLP, or applied machine learning roles.Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).Hands-on experience withLLMs and RAG architectures.Experience withvector databases(e.g., FAISS, Pinecone, Weaviate, Chroma).Knowledge of embeddings, similarity search, and retrieval strategies.Experience deploying AI models and services in cloud environments.Solid understanding of data security and governance principles.Nice to HaveExperience working with healthcare, insurance, legal, or regulatory text data.Familiarity with document ingestion pipelines (PDFs, scanned docs, OCR).Exposure to model monitoring, evaluation frameworks, and guardrails. .
