GenAI Engineer

Job Description GenAI Engineer Position Details Role: GenAI Engineer Experience: 5+ Years Location: Gurgaon, Pune, Noida Employment Type: Full-Time Salary Hike: Up to 15–25% on Current Fixed CTC Notice Period: Immediate Joiners or Candidates Serving Notice (Joining within 30 Days) About the Role We are looking for a highly skilled GenAI Engineer with strong hands-on experience in designing, developing, and deploying Generative AI solutions. The ideal candidate should have demonstrated end-to-end experience in building production-ready GenAI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and modern AI frameworks. Preference will be given to candidates who have successfully delivered impactful GenAI implementations and are currently working with well-known product or consulting organizations. Key Responsibilities Design, develop, and deploy enterprise-grade Generative AI applications. Build and optimize LLM-powered solutions using prompt engineering and orchestration frameworks. Develop Retrieval-Augmented Generation (RAG) pipelines for intelligent document search and question-answering systems. Implement vector embeddings and integrate vector databases such as Pinecone for semantic search. Fine-tune prompts and optimize model performance for business use cases. Build scalable machine learning and GenAI pipelines for production environments. Collaborate with business stakeholders, data scientists, and engineering teams to deliver AI-driven solutions. Monitor, evaluate, and improve LLM performance, accuracy, and reliability. Deploy AI/ML solutions on AWS cloud infrastructure following industry best practices. Contribute to architecture discussions and recommend innovative AI solutions for enterprise challenges. Mandatory Skills 5+ years of experience in Data Science, Applied Machine Learning, or Generative AI. Strong hands-on experience with end-to-end Generative AI projects. Expertise in Large Language Models (LLMs) and modern GenAI architectures. Hands-on experience with: LangChain Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Embeddings Pinecone or other Vector Databases Strong programming skills in Python. Experience with Machine Learning frameworks: Scikit-learn TensorFlow PyTorch Strong understanding of AI/ML lifecycle and model deployment. Preferred Skills Experience with Spark and/or Hadoop. Experience deploying ML and GenAI solutions on AWS. Exposure to productionizing LLM pipelines, monitoring, evaluation, and optimization. Experience with Palantir is an added advantage. Familiarity with MLOps and LLMOps practices. Domain experience in Finance, Banking, Insurance, Healthcare, or other data-intensive industries