Full Stack Engineer
Applied AI (Microsoft Full Stack AI / FDE)
1. Role Overview
We are seeking a visionary and hands-on Microsoft AI Lead to spearhead our Applied AI capability within the Microsoft Full Stack AI (FDE) practice. This leader will own the end-to-end strategy, delivery, and growth of five interconnected AI pillars — M365 Copilot Agents, Microsoft Native AI Agent Orchestration, Microsoft Foundry, Power Platform AI, and Responsible AI Governance — driving measurable business outcomes for enterprise clients. The ideal candidate combines deep Microsoft AI platform expertise with the executive presence and commercial acumen to build a high-performing team and drive growth.
2. Key Responsibilities
M365 Copilot Agents + Deploy
Lead design and deployment of Microsoft 365 Copilot agents (Declarative & Custom Engine Agents) across enterprise clients.
Define best practices for Copilot extensibility using Microsoft 365 Agents SDK, Graph connectors, and Teams AI Library.
Oversee adoption and change-management programmes to maximise Copilot ROI for clients.
Microsoft Native AI Agent Orchestration
Architect multi-agent solutions leveraging Azure AI Agent Service, Semantic Kernel, and AutoGen frameworks.
Drive development of orchestration patterns (sequential, parallel, handoff) for complex AI workflows.
Ensure seamless integration between agents, enterprise data sources, and downstream systems of record.
Microsoft Foundry (Azure AI Foundry)
Lead client engagements involving Azure AI Foundry for model fine-tuning, evaluation, and deployment at scale.
Build accelerators and reusable assets on the Foundry platform to reduce time-to-value.
Stay current with Foundry's model catalogue (OpenAI, Meta, Mistral, Phi) and advise clients on model selection.
3. Required Skills & Experience
15+ years of experience in technology consulting or enterprise software, with at least 5 years in AI/ML leadership roles.
Deep hands-on expertise across the Microsoft AI stack: Azure OpenAI Service, Azure AI Foundry, Semantic Kernel, Copilot Studio, Power Platform, and Microsoft 365.
Strong understanding of LLM architectures, RAG patterns, agentic workflows, and prompt engineering.
Experience delivering complex AI transformation programmes for clients in regulated industries.
Demonstrated ability to translate technical AI capabilities into compelling business value propositions.
Excellent executive communication, client relationship management, and stakeholder influence skills.
Strong commercial acumen — skills in deal structuring, SOW development, and contract negotiations.
4. Preferred Qualifications
Microsoft certifications: Azure AI Engineer Associate (AI-102), Azure Data Scientist (DP-100), Power Platform Solution Architect (PL-600).
Experience as a Microsoft Partner-side architect or having held roles within Microsoft (FTE/FDE/CSA).
Familiarity with MLOps pipelines, Azure Machine Learning, and model governance tooling.
Contributions to open-source AI projects or publications in AI/ML domains.
Experience with multi-cloud AI strategies and interoperability with AWS Bedrock or Google Vertex AI.