Azure AI Engineer

About

Design, build, and manage AI applications on Microsoft Azure, using Azure AI Foundry, Azure Machine Learning, Azure OpenAI Service, Azure AI Search (Knowledge Mining), and Cognitive Services.

Integrate AI models into applications, services, and processes as APIs.

Leverage SharePoint content for RAG and MCP integration—build pipelines that index enterprise documents, configure vector search, and ground Copilot responses with secure SharePoint data access.

Implement Responsible AI guardrails—set up safety filters, prompt moderation, content policies, and compliance checks; maintain auditability and incident playbooks.

Perform model fine‑tuning using JSONL datasets for generative AI/custom scenarios; manage prompt strategies, grounding, and evaluation.

Implement real‑time analytics with Azure Stream Analytics, Event Hub, and Azure Functions for streaming ingestion, transformation, and inference.

Monitor and optimize AI models for quality, latency, cost, drift, and fairness using Azure ML metrics, Application Insights, and custom telemetry; support A/B tests and safe rollback.

Conduct testing and QA (unit/functional, load/performance, safety tests, prompt safety, regression suites).

Document AI development—create runbooks, architecture diagrams, and operational playbooks for supportability and audits.

Stay current with AI advancements—evaluate new Azure capabilities (model catalog updates, agent orchestration, prompt engineering patterns).

Ensure compliance and security—adhere to data privacy regulations and enterprise policy; use Azure Key Vault, Managed Identity, Private Links, RBAC, Purview, and other security controls.

Provide technical leadership and strategic direction for AI initiatives; contribute to platform standards, best practices, and reusable components.

Qualifications

Required

• 3+ years in an Azure AI Engineer / Developer delivering production AI solutions.
• Graduate with 10+ years in Software engineering industry and competent in cloud native microservices development, event‑driven patterns with SharePoint/Teams development experience.
• Expertise in Microsoft Azure and AI services: Azure AI Foundry, Azure Machine Learning, Azure OpenAI Service, Azure AI Search (Cognitive Search), Cognitive Services.
• Proficiency in AI/ML and data‑driven analytics focused on model deployment, optimization, monitoring, and reliability.
• Programming experience in C# (APIs, SDKs, automation scripts, serverless functions).
• SharePoint Online experience for RAG pipelines and MCP integration—indexing, metadata enrichment, and secure access patterns.
• Strong competence with Microsoft Copilot, Copilot Studio, and the Copilot Agent Framework for agentic workflows and enterprise data integration.
• Prior experience in integrating with Microsoft Graph, SharePoint, Teams, and Power Platform; building Copilot plugins/skills grounded in enterprise content.