Define and own the end-to-end architecture for enterprise-scale GenAI AI solutions Design reference architectures reusable patterns and best practices for integrating GenAI into business applications Collaborate with domain leaders data scientists security and developers to align business requirements with scalable AI architectures Select and evaluate LLMs vector databases and orchestration frameworks based on performance compliance and cost trade-offs Architect RAG pipelines agentic workflows and multi-agent ecosystems for production-grade deployments Ensure security privacy and governance frameworks are embedded in AI systems from inception Drive adoption of cloud-native AI services Azure OpenAI AWS Bedrock and optimize for scalability and performance Guide teams in model lifecycle management including deployment monitoring retraining and drift handling MLOps Evaluate and recommend tools frameworks and protocols e g MCP LangChain LangGraph for robust interoperability Stay ahead of the curve on GenAI AI advancements regulations and enterprise adoption trends and translate them into actionable roadmaps - Grade Specific Bachelor s master s degree in computer science Statistics Engineering or related field Proven experience as an AI ML GenAI Architect designing large-scale AI ML systems Deep expertise in Python ecosystem ML DL frameworks PyTorch TensorFlow etc Robust knowledge of LLM architectures fine-tuning techniques LoRA PEFT adapters and deployment strategies Expertise in RAG pipelines embeddings and vector databases Elastic Pinecone Milvus etc Familiarity with agentic GenAI systems LangChain LlamaIndex AutoGen Crew ai LangGraph and Model Context Protocol MCP Experience in cloud-native architecture AWS Azure and container orchestration Docker Kubernetes Solid understanding of MLOps principles CI CD for ML observability retraining pipelines and model governance Strong ability to bridge business and technology communicating complex AI strategies to stakeholders Deep understanding of Responsible AI principles and ability to embed governance compliance and ethical frameworks into GenAI solution design Bonus Experience in enterprise-scale AI adoption across Telecom industries

📌 Ai Ml Architect (Karnataka)
🏢 Capgemini Engineering
📍 Karnataka