DE&A - AIML - Machine Learning - Other

AI Architect Experience: 12–16 Years Location: Pune / Bengaluru / Hyderabad Looking for a workplace where people realize their full potential, are recognized for the impact they make, and enjoy the company of the peers they work with? Welcome to Zensar! Read on for more details on the role and about us. What's this role about? We are seeking an experienced AI Architect to lead the design and implementation of enterprise-scale AI, Generative AI, and Agentic AI solutions. The ideal candidate will be responsible for defining AI architecture strategy, designing scalable AI platforms, and driving the adoption of intelligent solutions that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents. The role requires close collaboration with business stakeholders, AI engineers, data scientists, and delivery teams to transform business challenges into practical AI solutions. The candidate should possess expertise in architecting GenAI applications, conversational AI, knowledge assistants, agent-based workflows, and AI governance frameworks while ensuring scalability, security, and responsible AI adoption. Skills required to contribute: Required Skills 10+ years of overall IT experience with significant experience in AI/ML solution architecture. Strong expertise in designing and implementing Generative AI, Machine Learning, and Agentic AI solutions. Hands-on experience with Large Language Models (LLMs) such as GPT, Gemini, Claude, Llama, or similar foundation models. Experience architecting RAG (Retrieval-Augmented Generation) solutions using vector databases and enterprise knowledge repositories. Strong understanding of Agentic AI architectures, AI Assistants, AI Copilots, and multi-step orchestration workflows. Experience with AI application frameworks such as LangChain, LangGraph or similar Agentic AI frameworks. Expertise in Prompt Engineering, AI workflow design and LLM application architecture. Strong knowledge of AI evaluation, observability, governance, and responsible AI practices. Experience with Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, or Scikit-Learn. Experience leveraging cloud-based AI services on Azure, AWS, or Google Cloud Platform. Understanding of vector databases, semantic search, embeddings, and enterprise knowledge management solutions. Experience integrating AI solutions with enterprise applications, APIs, and business workflows. Strong customer engagement, solutioning, architecture review, and stakeholder management skills. Ability to provide technical leadership and mentor AI engineering teams. Good to Have Experience with Agentic AI frameworks such as LangChain, LangGraph or similar platforms. Experience implementing enterprise chatbots, copilots, or AI assistants. Exposure to MLOps practices and AI observability tools. Experience working with Azure AI Foundry, AWS Bedrock, or Google Vertex AI. Domain experience in Retail, Banking, Insurance, Manufacturing, or Healthcare. Cloud or AI-related certifications. Educational Qualification Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence or a related field. Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence or a related field.