AI Architect

Overview We are seeking a highly skilled and experienced Azure OpenAI Architect to lead the design and implementation of end-to-end Generative AI systems. This role goes beyond building AI models—it involves architecting robust, scalable, and secure AI-powered applications and services across the full technology stack. The ideal candidate will combine deep expertise in AI/ML, modern software engineering practices, and cloud architecture to deliver impactful business solutions using Azure OpenAI and related technologies. You will play a pivotal role in guiding technical strategy, integrating LLMs, overseeing system design and development, and ensuring seamless deployment and operation of AI-powered applications. Architect End-to-End AI Solutions : Lead the design of comprehensive AI systems from data ingestion and model orchestration to full-stack applications and secure deployment pipelines. Cloud Architecture & Infrastructure : Design and manage scalable Azure cloud infrastructure, including networking, resource provisioning, monitoring, and cost optimization. Implement secure architectures using Azure Active Directory, Managed Identities, Role-Based Access Control (RBAC), Key Vault, and compliance with organizational and regulatory standards. Gen AI & LLM Integration : Design and deploy Generative AI applications using Azure OpenAI Service, Open Source LLMs (e.g., Llama2, Mistral), and frameworks like LangChain, Semantic Kernel, and vector databases. Software Engineering : Develop full-stack AI applications using Python (FastAPI) for backend services and ReactJS for user interfaces. DevOps & CI/CD : Automate infrastructure and deployment workflows using Azure DevOps, GitHub Actions, or Terraform for continuous integration, delivery, and monitoring. Data Engineering : Build and manage data pipelines for ingesting, processing, and enriching structured and unstructured data using services like Azure Data Factory, Azure Synapse, and Azure AI Document Intelligence. Search & RAG Implementation : Implement advanced search features and Retrieval-Augmented Generation (RAG) pipelines using Azure AI Search, vector stores, embeddings, summarization, and query transformation. Monitoring & Optimization : Continuously monitor solution performance and availability, and optimize AI workloads across the stack. Collaboration & Leadership : Work with data scientists, engineers, product managers, and business stakeholders to align solutions with organizational goals. Innovation & Best Practices : Stay ahead of AI trends and Azure capabilities, promoting best practices in architecture, coding, and system design. 8+ years of experience in IT, with 5+ years focused on AI/ML engineering or AI system architecture. ~ Proven track record in designing and delivering end-to-end AI/GenAI solutions in production environments. ~ Strong proficiency with Azure Cloud Platform , including services like: ~ Azure OpenAI, Azure AI Search, Azure App Services, Azure Functions, Azure Key Vault ~ Azure Cognitive Services (Speech, Vision, Document Intelligence) ~ Azure Kubernetes Service (AKS), Azure Container Apps ~ Deep understanding of cloud networking, security, and identity/access management on Azure. ~ Hands-on experience with DevOps tools (Azure DevOps, GitHub Actions, Terraform, Bicep). ~ Expertise in backend development using Python (FastAPI, Flask) and frontend development using ReactJS . ~ Familiarity with LLMs, Transformer architectures , vector search, LangChain, and RAG pipelines. ~ Experience with vector databases (e.g., Strong skills in data engineering , working with structured/unstructured data pipelines and ETL tools. ~ Microsoft Certified: Azure Solutions Architect Expert, Azure AI Engineer Associate). ~ Passion for innovation and a track record of delivering enterprise-grade AI solutions. Experience with Kubernetes , MLflow , or Ray for distributed training/deployment. Familiarity with SaaS AI product development or MLOps pipelines . Exposure to multi-modal GenAI (text, image, audio, video).