About the position
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.
Desired Skills:
- Context Protocol (MCP)
- Auzure
- Data & AI practice. Enterprise-grade AI agents
Desired Qualification Level:
