Azure AI Engineer

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).