Full Stack Engineer Ai

Job Description

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

• Deep 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.