Technical Architect-Azure AI

Job Summary We are seeking a hands-on, innovative Azure AI Architect to join our advanced AI engineering team. In this role, you will work at the forefront of applied AI extending Microsoft Copilots, building Retrieval-Augmented Generation (RAG) pipelines, and crafting intelligent AI agents for real-world business applications. You will leverage Azure AI Studio, Semantic Kernel, Azure AI Search, and other services across the Microsoft AI stack. Key Responsibilities Pre-Sales & Client Engagement Act as the AI subject matter expert in client conversations, workshops, and solution envisioning sessions. Support proposal development, architecture documentation, and effort estimation for AI projects. Translate complex business needs into high-level and detailed technical architecture diagrams and blueprints. Design Azure AI Solutions Define architectural patterns for integrating LLMs, generative AI, RAG pipelines, vector databases (e.g., Azure AI Search, FAISS), and orchestration frameworks (e.g., Semantic Kernel, LangChain). Support team in building Azure Cost estimates for various types of solution archetypes, provide guidance on selecting the most cost-effective Azure AI service configurations (e.g., model size, region, compute SKUs). Ensure scalability, security, governance, and compliance are foundational in all designs. Copilot Extension & Customization Provide subject matter expertise in using Azure AI Studio to extend and fine-tune Microsoft 365 Copilots and custom business Copilots. Integrate enterprise data and logic to create domain-specific copilots aligned with customer workflows. Apply prompt engineering and grounding strategies to enhance context awareness and action-taking capabilities. Advanced AI Pipeline Development Build retrieval-augmented generation (RAG) pipelines and advanced RAG pipelines (such as GraphRAG) using Azure AI Search, Cognitive Search, and Semantic Kernel. Design chunking, embedding, ranking, and post-processing strategies to optimize search relevance and model responses. Connect unstructured and structured content (e.g., PDFs, Word, Excel, D365 data) to GenAI models for personalized search and Q&A. Leverage Azure Custom Skills to enrich data across the pipeline to build enterprise-grade scaled AI solutions AI Agent Design and Orchestration Design and deploy multi-step AI agents that reason, retrieve, and take action based on dynamic workflows. Develop solution archetypes (e.g., knowledge assistants, workflow copilots, policy advisors) powered by Semantic Kernel or Azure OpenAI Function Calling. Implement agent memory, state management, and tool integration (APIs, plugins, functions). AI Lifecycle Engineering Automate deployment using Azure DevOps, CI/CD, and containerization where needed. Monitor model outputs for relevance, accuracy, and alignment to responsible AI principles. Collaborate with data engineers, solution architects, and UX designers for full-stack deployment. Technical Leadership & Delivery Oversight Provide technical leadership on AI implementations, including model training, inferencing, and MLOps integration. Conduct architecture reviews, code walkthroughs, and design governance. Collaboration and Communication Collaborate cross-functionally (software engineering, product, design, etc.) to align AI solutions with business goals. Document and communicate technical designs, roadmaps, and updates to both technical and non-technical stakeholders. Research and Innovation Stay current on emerging AI/ML and Generative AI trends, frameworks, and tools, recommending advancements that can enhance our AI initiatives. Champion a culture of continuous learning and experimentation across the organization. Qualifications Education: Bachelor s or Master s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience). Experience: 5+ years of hands-on AI/ML engineering experience, with a strong focus on Microsoft Azure. Proven experience with Generative AI models (LLMs, text or image generation) is highly desirable. Required Skills: 5+ years of experience in AI/ML solution engineering, with a focus on Microsoft Azure AI services. Proficient with: Azure AI Studio, Azure OpenAI Service, Azure Cognitive Search / AI Search Semantic Kernel, LangChain (preferred), or similar orchestration frameworks Prompt engineering, grounding techniques, embedding models Experience building RAG-based applications and deploying GenAI models in production. Strong Python and/or C# skills for SDK use and orchestration logic. Familiarity with REST APIs, Azure Functions, and plugin development. Azure certifications (e.g., Azure AI Engineer Associate, Solutions Architect). Experience with Copilot Studio, Graph RAG, or Microsoft Fabric integrations. Knowledge of Responsible AI, prompt safety, and guardrail implementation. Nice to have skills: Soft Skills: Excellent problem-solving and analytical abilities. Strong communication and collaboration skills. Ability to work in a fast-paced, agile environment, managing multiple priorities effectively.