[Hiring] Azure AI Engineer @Apptad, Inc.

Role Description

• Azure AI Generative AI Experience building GenAI applications using Azure OpenAI Copilot RAG architectures, prompt engineering, evaluation frameworks, and grounding citation mechanisms.
• Backend Development: Strong experience in CNET or Python, REST APIs, microservices, Azure Functions, Container Apps, Logic Apps, and scalable service development.
• Azure Cloud Engineering: Hands-on experience with Azure App Services, Azure AI Search, Managed Identity, Key Vault, Storage Accounts, APIM, Monitoring, and Container-based deployments. Multiple workstreams focus on content ingestion, MCP integration, and telemetry.
• AI Search RAG Implementation: Experience with document ingestion, indexing, chunking, retrieval optimization, embeddings, citations, and search quality validation. Project heavily relies on content ingestion and retrieval grounded responses.
• Software Engineering DevOps: CICD, GitHub, ADO, code reviews, testing, release management, automation, and deployment pipelines. Engineering discussions highlight grooming, production readiness, release validation, and operational ownership.
• GitHub Copilot & VS Code Copilot for AI Assisted Development: Hands-on experience using GitHub Copilot and VS Code Copilot Chat for code generation, code review, refactoring, unit test generation, debugging, documentation generation, API integration development, and developer productivity optimization. Ability to effectively use AI assisted development workflows while maintaining code quality, security, and engineering best practices.
• Telemetry Production Operations: Ability to troubleshoot production workloads, analyze telemetry, monitor reliability, and perform root cause analysis. Content observability, ingestion monitoring, ICM processes, and dashboards are active priorities.
• Responsible AI Security: Knowledge of SDL, threat modeling, Responsible AI reviews, compliance processes, and secure design patterns.
• Communication & Cross Team Collaboration: Ability to work across Product Engineering, Content, Copilot, and Partner teams; participate in feature reviews, design discussions, and roadmap execution.

Qualifications

• Generative AI
• Open AI
• Azure Cloud Architecture
• Copilot

Requirements

• Microsoft 365 Copilot Extensibility: Declarative Agents, Copilot plugins, agent orchestration, and Copilot native integrations.
• Model Context Protocol (MCP): Experience building or integrating MCP servers and external knowledge systems.
• Voice Multimodal AI: Experience with speech, voice agents, conversational AI, and multimodal experiences.
• Power Platform: Power Automate, Power Apps, Logic Apps, and workflow automation for operational experiences.
• Data Engineering Analytics: Kusto, Power BI, Fabric, telemetry pipelines, dashboards, and reporting.
• Evaluation Frameworks for AI: Experience creating evaluation datasets, regression testing, hallucination checks, relevance testing, and multiturn conversation evaluation.