Generative AI Engineer - LLM Models

Title : GenAI Engineer

Location : Bengaluru, Chennai, Hyderabad, Pune, Vadodara, Gujarat

Years of Exp : 7 to 12 Years

Employment Type : Full-time

Key Responsibilities

• Architect and develop Generative AI-based applications using Azure OpenAI, Azure ML Studio, Azure Cognitive Search, and Azure Document Intelligence.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise search, knowledge management, and domain-specific Q&A systems.
• Integrate Large Language Models (LLMs) into production applications with attention to performance, scalability, and governance.
• Design intelligent workflows using LangChain, LlamaIndex, and Semantic Kernel for orchestrating multi-step AI interactions and agent behaviors.
• Collaborate with data scientists, ML engineers, and DevOps to deploy, monitor, and manage cloud-native AI solutions.
• Incorporate OCR capabilities and document understanding pipelines using Azure Form Recognizer and Document Intelligence.
• Ensure AI models and pipelines comply with enterprise standards, data privacy, and responsible AI principles.
• Lead proof-of-concepts (PoCs), rapid prototypes, and solution demos to validate GenAI use cases across departments.
• Maintain a strong understanding of evolving LLM architectures, foundation models, and emerging GenAI techniques.
• Contribute to technical documentation, best practices, and reusable solution accelerators.
  

Required Qualifications

• Bachelor's or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  

Proven Experience With Azure AI Services, Including

• Azure OpenAI
• Azure Machine Learning Studio
• Azure Cognitive Search
• Azure Form Recognizer / Document Intelligence
• Strong Python development skills, especially in the context of LLM pipelines and prompt engineering.
• Expertise with GenAI libraries and tools such as:
• LangChain
• LlamaIndex
• Semantic Kernel
• Familiarity with RAG architecture, vector databases (e.g., FAISS, Redis, Azure Cognitive Search), and embedding models.
• Experience with containerization (Docker) and cloud-native deployment pipelines using Azure DevOps, Kubernetes, or Terraform.
• Understanding of Responsible AI principles, including bias mitigation, explainability, and model monitoring.
• Excellent problem-solving and communication skills; ability to work in cross-functional agile teams.
  

Preferred Qualifications

• Experience integrating agent-based frameworks for autonomous task execution and multi-agent collaboration.
• Knowledge of other GenAI ecosystems like Hugging Face Transformers, Anthropic Claude, or Mistral models.
• Background in enterprise content management, knowledge graphs, or intelligent document processing (IDP).
  

Azure Certifications Such As

• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Certified: Azure Solutions Architect Expert
  

What We Offer

• Opportunity to work on groundbreaking AI initiatives at enterprise scale.
• Collaborative, fast-paced, and innovation-driven team culture.
• Flexible work arrangements (remote/hybrid).
• Competitive compensation, equity options, and comprehensive benefits.