Senior AI Engineer (Microsoft Copilot & AI Platform)

Aegasis Labs is an AI-first agent development company specializing in building AI agents, Retrieval-Augmented Generation (RAG) systems, and AI-native platforms for startups and enterprises across healthcare, fintech, sports, and enterprise SaaS sectors. With offices in London and Lahore, we are seeking a Senior AI Engineer for an embedded role within an enterprise client’s IT Solutions Department. This position offers the opportunity to lead AI solution delivery end-to-end in a regulated enterprise environment, focusing on Microsoft 365 Copilot and evolving towards Azure AI Foundry and Azure Databricks platforms. Success in this role is measured by the tangible business value delivered rather than the volume of AI agents created.

Key Responsibilities
- Own the complete architecture and delivery lifecycle across Microsoft 365 Copilot, Copilot Studio, Power Platform, Azure AI Foundry, and Azure Databricks under a managed services framework.
- Collaborate with business and IT stakeholders to identify, prioritize, and validate AI use cases, establishing business cases and KPIs before development begins.
- Design and implement Copilot agents (including declarative agents), custom connectors, MCP integrations, Power Platform workflows, and Azure-based RAG and agentic AI solutions, progressing from proof of concept to production deployment.
- Ensure all AI solutions comply with security and governance standards using Microsoft Purview, Entra ID, and Data Loss Prevention (DLP) tools, aligned with National Cybersecurity Authority (NCA) requirements.
- Define and enforce architecture standards, reference patterns, and Application Lifecycle Management (ALM) practices across Development, Testing/UAT, and Production environments.
- Manage the ongoing service delivery including SLAs, monitoring, incident management, and change control through the client’s IT Service Management (ITSM) processes.
- Oversee Copilot Studio capacity, Azure resource consumption, and token usage, providing regular performance and value realization reports.
- Advise on Microsoft AI roadmap developments and facilitate knowledge transfer to internal teams.
- Support broader IT strategy initiatives such as Enterprise Project Management (EPM) process automation.

Required Qualifications
- Minimum of 6 years’ experience in AI/ML or Microsoft solution engineering with proven production deployments.
- Hands-on expertise with Microsoft 365 Copilot, Copilot Studio (agents and custom connectors), Azure OpenAI Service, and Azure AI Foundry.
- Demonstrated delivery of at least two RAG or agentic AI solutions in enterprise settings.
- Proficiency with Power Platform components (Power Automate, Power Apps, Dataverse) and Microsoft Graph API.
- Strong programming skills in Python and REST API development, including experience with large language model (LLM) evaluation and prompt engineering.
- Deep understanding of AI governance and security frameworks, including Microsoft Purview, Entra ID, and compliance with NCA ECC, CCC, and DCC controls.
- Bachelor’s degree in Computer Science, Information Systems, AI, or a related discipline.
- Fluency in both Arabic and English, with the ability to communicate complex technical concepts effectively to senior stakeholders.
- Active possession of at least two of the following Microsoft certifications is mandatory:
1. Azure AI App and Agent Developer Associate (AI-103) or Azure AI Engineer Associate (AI-102)
2. Azure Databricks Data Engineer Associate (DP-750)
3. Agentic AI Business Solutions Architect (AB-100) or equivalent AI Business Solutions certification
4. AI Agent Builder Associate (AB-620, Copilot Studio)
Candidates must provide a Microsoft Learn transcript link verifying their certifications; applications lacking two qualifying certifications will not be considered.

Preferred Qualifications and Benefits
- Experience with Azure Databricks and Azure AI Search.
- Familiarity with Semantic Kernel or AutoGen frameworks.
- Knowledge of Azure DevOps or GitHub Actions for CI/CD pipelines.
- Additional certifications such as AB-410, AI-300, or SC-500 are advantageous.

Interview Process
The selection process includes:
1. Recruiter screening and certification verification.
2. Technical deep dive focusing on two production AI solutions you have delivered.
3. Architecture and governance evaluation.
4. Stakeholder engagement round to assess communication and alignment skills.

This role offers a unique opportunity to shape AI innovation within a regulated enterprise, driving impactful solutions that align with strategic business goals.