MS Generative AI – Technical Architect

• Architecture & Solution Design
• Own the technical blueprint and architectural governance for Generative AI initiatives across one or more enterprise workstreams.
• Design end‑to‑end GenAI solutions covering
• Application architecture
• AI/ML & LLM orchestration
• Agentic and multi‑agent designs
• Data ingestion, storage, and retrieval (RAG patterns)
• Drive concept‑to‑design‑to‑system architecture for AI‑enabled applications.
• Ensure solution alignment across application, infrastructure, data, and AI layers.

• Generative AI & AI/ML Leadership
• Architect and guide development of GenAI use cases including
• Copilots and AI assistants
• Conversational interfaces
• Document intelligence
• Automation using LLMs and agents
• Define patterns for prompt engineering, RAG, vector databases, and agent frameworks.
• Evaluate and integrate LLMs (OpenAI and Azure OpenAI services) into enterprise solutions.

• Microsoft Technology & Cloud Architecture
• Architect solutions using the Microsoft Azure ecosystem, including
• Azure OpenAI
• Azure AI Services
• Azure Machine Learning
• Azure Kubernetes Service (AKS)
• Azure App Services & Functions
• Ensure cloud‑native, scalable, and secure architectures following Azure Well‑Architected Framework.

• Enterprise Governance & Security
• Enforce enterprise compliance, security, and standardization across GenAI implementations.
• Define governance models for
• AI usage and responsible AI compliance
• Data privacy and security
• Model lifecycle management
• Collaborate with security and risk teams on AI governance and ethical AI frameworks.

• Technical Mentorship & Stakeholder Collaboration
• Act as a technical authority for AI/GenAI initiatives.
• Collaborate with
• Business stakeholders
• Product owners
• Data scientists and ML engineers
• Application development teams
• Mentor architects and senior engineers on AI architecture best practices.

Mandatory Skills &

• Core Technical Background
• Strong prior hands‑on experience in .NET technology stack, including
• C# / ASP.NET / .NET Core
• Enterprise application architecture
• REST APIs and microservices
• Proven experience as a Technical Architect in large‑scale enterprise environments.

• AI / ML / GenAI Expertise
• Hands‑on experience architecting AI/ML and Generative AI solutions.
• Practical understanding of
• Large Language Models (LLMs)
• Prompt engineering
• Retrieval‑Augmented Generation (RAG)
• Vector databases
• Agentic AI design patterns

• Preferred / Good to Have
• Experience building Copilot‑style applications or enterprise AI assistants.
• Knowledge of responsible AI frameworks and AI risk governance.
• Exposure to multi‑cloud or hybrid architectures.
• Azure certifications (Solution Architect, AI Engineer, or equivalent).