Gen AI Engineer

Generative AI Engineer (3–5 Years Experience)Role OverviewWe 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 Responsibilities

• Design, build, and deploy RAG-based AI solutions using large language models for document analysis, summarization, and intelligent automation.


• Develop and optimize retrieval pipelines leveraging 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 & Experience

• 3–5 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 with LLMs and RAG architectures.


• Experience with vector 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 Have

• Experience 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.