About

• About the Role
• As an Azure AI Engineer (Generative AI specialization), you will design, develop, and deploy AI, ML, and agentic AI solutions within the Azure ecosystem. You’ll collaborate with cross-functional teams to build enterprise-grade AI applications leveraging Large Language Models (LLMs), Generative AI, and Agentic AI architectures.
• Key Responsibilities

AI Solution Design

• Translate business requirements into full-stack Azure AI solutions using Azure AI Services, Azure AI Search, Azure OpenAI, Cosmos DB, Copilot Studio, and RAG patterns.
• Design multi-step prompt workflows, intelligent agents (task/role-based), and apply Responsible AI principles.
• Build dynamic UIs for chatbots and dashboards using React.js.

AI Development

• Orchestrate prompts and tools using PromptFlow and Azure AI Foundry.
• Extend Microsoft Copilots via Copilot Studio, Graph Plugins, and build custom AI agents using plugin architecture, API function calling, and memory constructs.
• Implement LLM-based orchestration with LangChain, Semantic Kernel, or similar frameworks.
• Deploy solutions using Azure Functions, Container Apps, Blob Storage, and Cosmos DB.
• Utilize Git/Azure DevOps for CI/CD and containerized deployments.

Monitoring & Observability

• Define metrics for prompt effectiveness and model behavior.
• Implement logging, tracing, and observability using Azure App Insights and Cosmos DB Logs.
• Troubleshoot performance bottlenecks and mitigate hallucinations/data drift.

Data Governance

• Collaborate with data engineers on pipelines for chunking, enrichment, and reinforcement learning.
• Ensure data quality, integrity, and security throughout the lifecycle.

Collaboration & Innovation

• Communicate technical designs and updates to stakeholders.
• Stay current on Generative AI, Agentic AI, and emerging frameworks.
• Promote continuous learning and experimentation.
• Qualifications
• Education: Bachelor’s in computer science, Engineering, or related field (or equivalent experience).

Experience

• 4+ years in AI/ML engineering with production-grade deployments.
• 2.5+ years hands-on with Azure OpenAI or similar LLM APIs.
• Expertise in Python, LangChain, Semantic Kernel, PromptFlow, and cloud-native design.
• Experience with Azure AI Services, Copilot Studio, AI Foundry, Cosmos DB, and containerization (Docker/Kubernetes).
• Knowledge of LLMOps, prompt tuning, RAG, and Responsible AI.

Preferred

• Azure certifications (AI Engineer Associate, Solutions Architect).
• Experience with GraphRAG, caching, reinforcement learning architectures.
• Proficiency in React.js and BI tools (Power BI, Tableau).