Enterprise Architect (DFS)

• Design and architect enterprise-grade Generative AI and Agentic AI solutions using Microsoft Foundry.
• Lead the development and deployment of AI agents RAG pipelines LLM-powered applications multi-agent workflows and enterprise AI automation solutions.
• Architect secure scalable resilient and production-ready AI solutions using Azure OpenAI Microsoft Foundry Azure AI Search Azure Storage Azure Cosmos DB Azure Functions Azure Kubernetes Service API Management Azure Monitor Application Insights and related Azure services.
• Define reference architectures reusable design patterns accelerators and best practices for enterprise Generative AI and Agentic AI adoption.
• Collaborate with cross-functional teams to integrate AI solutions into existing systems.
• Lead AI solution design discussions technical workshops architecture reviews proof-of-concept engagements and production-readiness assessments.
• Stay updated with advancements in Generative AI Agentic AI Microsoft Foundry Azure AI services and emerging AI architecture patterns.
• Provide technical leadership and mentorship to the AI development team.
• Optimize AI solutions for performance scalability reliability accuracy latency observability and cost.
• Ensure the implementation of best practices in AI and ML development.
• Work closely with stakeholders to understand business needs and translate them into technical solutions.

Must Have Skills:

• Strong hands-on experience designing and implementing production-grade Generative AI and Agentic AI solutions using Azure AI Foundry / Microsoft Foundry.
• Strong experience with Azure OpenAI Microsoft Foundry Foundry Agent Service Azure AI services and Azure AI SDKs.
• Strong understanding of RAG architecture embeddings vector search chunking strategies retrieval optimization grounding re-ranking prompt engineering and hallucination mitigation.
• Experience architecting enterprise integrations with APIs databases knowledge repositories ITSM platforms monitoring systems automation platforms and enterprise applications.
• Experience with Azure AI Search Azure Storage Cosmos DB Key Vault Entra ID RBAC private networking API Management Azure Monitor Application Insights and Log Analytics.
• Strong understanding of LLMOps / GenAIOps including model evaluation prompt management observability tracing monitoring versioning governance and operational support.
• Proven experience leading complex AI/ML Generative AI Agentic AI or cloud-native AI projects for large enterprise customers.
• Ability to assess business requirements and recommend the right architecture framework model deployment approach and governance model.
• Excellent problem-solving communication stakeholder management consulting and technical leadership skills.
  
  

  Preferred Skills:

  • Experience with AI model deployment and monitoring.
  • Knowledge of data engineering and data preprocessing techniques.
  • Familiarity with AI ethics and responsible AI practices.

Qualifications:

• Bachelors or Masters degree in Computer Science Engineering Data Science Artificial Intelligence or a related field.
• Hands-on experience in AI/ML Generative AI Agentic AI cloud-native architecture and enterprise solution design.
• Strong proficiency in building ai agents using LangGraph or MS SDK in Microsoft Foundry.
• Strong understanding of deep learning NLP LLMs multimodal AI OCR speech-to-text text-to-speech and image processing techniques.
• Hands-on experience in designing and architecting Gen AI and Agentic AI solutions or tools (preferably for infrastructure use-cases) for large enterprise customers.
• Ability to build new solutions from scratch create reusable accelerators and drive innovation-led delivery.
• Hands-on experience with LLMs RAG agentic automation and agent frameworks like Langchain Lang graph Azure AI Foundry / Microsoft Foundry.
• Hands-on experience in Gen AI observability & monitoring via tools like Lang Smith
• Extensive experience in Prompt Engineering and ability to design and build Prompt libraries for various scenarios applicable in Infrastructure.
• Thorough understanding of Responsible AI best practices and standards and experience of implementing them in Gen AI/agentic ai related projects
• Proven track record of leading and delivering complex AI/ML projects.
• Excellent problem-solving skills and ability to work in a fast-paced environment.
• Strong communication and collaboration skills.