About the Role :

We are seeking a highly experienced Generative AI Architect to define and drive the enterprise-wide architecture and implementation of Generative AI solutions.

The candidate will be responsible for designing scalable, secure and high-performing AI architectures leveraging LLMs, Azure Cloud, Microsoft Copilot and Retrieval-Augmented Generation (RAG).

The role requires strong technical expertise, architectural leadership and the ability to translate business requirements into robust AI solutions.

Key Responsibilities :

- Define and own the end-to-end architecture and technology roadmap for enterprise Generative AI solutions.

- Design scalable LLM-based architectures leveraging Azure OpenAI and other Azure AI services.

- Architect enterprise-grade RAG solutions, covering data ingestion, chunking, embeddings, vector databases, retrieval optimization and response generation.

- Design and implement Microsoft Copilot integrations and customized enterprise Copilot solutions.

- Establish architectural standards, design principles and best practices for GenAI adoption.

- Drive model selection, prompt engineering, fine-tuning strategies and LLM performance optimization.

- Design secure and scalable AI solutions with appropriate governance, access controls, data privacy and responsible AI practices.

- Evaluate emerging GenAI technologies, frameworks and platforms to identify opportunities for enterprise adoption.

- Provide technical leadership to engineering teams and oversee solution design, development and deployment.

- Collaborate with business stakeholders, product teams and senior leadership to align AI architecture with organizational objectives.

- Define standards for observability, model evaluation, latency, scalability and cost optimization.

Required Skills & Qualifications:

- 12 - 14 years of overall experience in software engineering, solution architecture, AI/ML or related domains.

- Strong expertise in Generative AI, LLMs and enterprise AI solution architecture.

- Extensive experience designing and implementing RAG-based solutions.

- Strong hands-on experience with Microsoft Azure Cloud and Azure OpenAI Service.

- Experience architecting Microsoft Copilot and Copilot Studio solutions.

- Strong proficiency in Python and AI application development.

- Expertise in vector databases, embedding models, semantic search and advanced retrieval techniques.

- Understanding of LLM orchestration frameworks such as LangChain, LlamaIndex or Semantic Kernel.

- Experience with cloud architecture, distributed systems, API integrations and microservices.

- Strong understanding of AI security, governance, responsible AI and enterprise deployment practices.

- Proven experience in defining technical architecture, leading engineering teams and driving large-scale AI implementations.