Azure AI Developer – Microsoft Foundry
The Senior Azure Ai Developer Sits at the Critical Intersection of Software Engineering, Applied Ai, and Solution Delivery. You Will Be Responsible for Designing, Building, and Operationalizing Enterprise-grade Ai Solutions Using Microsoft Azure Ai Foundry and the Broader Azure Ai Ecosystem. This Role Requires a Balance of High-level Architectural Thinking and Deep, Hands-on Development Capability to Turn Complex Business Problems into Scalable, Production-ready Ai Systems.
As a senior member of the team, you will lead AI workstreams, mentor junior developers, and contribute to the evolution of AI platform standards within the Data & AI practice.
Key Responsibilities
Ai Solution Design & Orchestration
Agentic Systems: Design, deploy, and orchestrate enterprise-grade AI agents and multi-agent systems.
Framework Implementation: Utilize Foundry Agent Service and MCP-compatible patterns to build interoperable AI tools.
Scaling & Security: Secure and monitor AI systems using Azure App Service and containerized deployment models to ensure enterprise reliability.
Architecture Standards: Contribute to the development of delivery standards and best practices for the Data & AI practice.
Development & Operationalization
Hands-on Engineering: Build and maintain production-ready code for AI solutions within the Azure ecosystem.
End-to-End Delivery: Oversee the full lifecycle of AI solution delivery, from initial design through to operationalization.
Platform Expertise: Leverage the full Azure AI Foundry suite to create robust, scalable applications.
Leadership & Stakeholder Management
Strategic Advisory: Work directly with client stakeholders to translate business requirements into technical AI architectures.
Mentorship: Lead technical workstreams and provide guidance and mentorship to other developers.
Collaborative Delivery: Partner with cross-functional teams to ensure AI systems align with broader enterprise technology goals.
Technical Requirements
Platform Mastery: Extensive experience with Microsoft Azure AI Foundry and the Azure AI ecosystem.
Agentic Workflows: Deep understanding of AI agents, multi-agent orchestration, and the Model Context Protocol (MCP).
Cloud Infrastructure: Proficiency in Azure App Service, containerization (Docker/Kubernetes), and cloud-native deployment models.
Software Engineering: Strong background in software engineering principles, specifically applied to AI and data-heavy applications.
Security & Monitoring: Experience implementing security protocols and monitoring frameworks for live AI deployments.
Professional Attributes
Architectural Thinking: Ability to see the "big picture" while maintaining focus on technical execution.
Problem Solver: Proven ability to turn ambiguous business challenges into structured, scalable technical solutions.
Effective Communicator: Able to explain complex AI concepts to both technical peers and non-technical client stakeholders.