Description : We are looking for an accomplished and visionary AI Architect with deep expertise in designing and leading the development of AI Agents and Retrieval-Augmented Generation (RAG) platforms. The ideal candidate will have a strong background in GenAI frameworks, enterprise AI solution architecture, and hands-on experience with Copilot Studio, Power Automate, and cloud-native AI services. This role will drive the strategic direction, architecture, and governance of AI solutions across the organization.

Key Responsibilities :

- Define the end-to-end architecture for AI Agents and RAG-based solutions, ensuring scalability, reliability, and security.

- Lead the design and implementation of advanced AI platforms, integrating vector databases, embedding models, and document retrieval systems to enhance LLM capabilities.production grade

- Architect seamless integration of GenAI solutions with Copilot Studio, Power Automate, and other enterprise workflow tools.

- Set technical standards, best practices, and governance frameworks for AI/ML development and deployment.

- Collaborate with executive leadership, product owners, and cross-functional teams to align AI strategy with business objectives.

- Oversee the optimization of GenAI models for performance, latency, and accuracy in production environments.

- Evaluate and recommend emerging technologies, frameworks, and tools in LLMs, agentic workflows, and GenAI.

- Mentor and guide development teams, fostering a culture of innovation, knowledge sharing, and technical excellence.

- Ensure compliance with enterprise data governance, security, and regulatory requirements in all AI applications.

- Drive the adoption of MLOps and CI/CD pipelines for robust AI model lifecycle management.

Required Qualifications :

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, or related field; advanced degree preferred.

- 12+ years of experience in AI/ML solution architecture and development, with at least 3 years focused on Generative AI and enterprise-scale deployments.

- Proven expertise in architecting AI Agents and RAG solutions using frameworks such as LangChain, LangGraph, Semantic Kernel, Haystack, or similar.

- Deep hands-on experience with Copilot Studio, Power Automate, Dataverse, Microsoft Fabric, and cloud AI services (Azure OpenAI, Azure AI Studio,,Azure Ml Foundry Azure Functions, Azure Kubernetes Service, Azure Cosmos DB, etc.).

- Strong proficiency in Python, JavaScript frameworks, REST API design, and modern database technologies (e.g., MongoDB, vector stores like FAISS, Pinecone, Weaviate).

- Demonstrated experience with cloud platforms (Azure, AWS, GCP) and deploying GenAI solutions at enterprise scale.

- Expertise in prompt engineering, model fine-tuning, evaluation methodologies, and building robust AI guardrails.

- In-depth knowledge of enterprise data governance, security, compliance, and risk management in AI applications.

- Experience implementing MLOps, CI/CD pipelines, and best practices for AI model deployment and monitoring.

- Exceptional communication, leadership, and stakeholder management skills.