What are the responsibilities and job description for the Azure AI Engineer position at Canvendor?
Role : Azure AI Engineer
Location : East Brunswick, NJ (Hybrid)
Type: Contract
JD :
- 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.
Essential Requirements (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.