PFB the JD for Technical PM
Technical Project Manager for Microsoft Copilot and Azure AI Solutions, you will shape and drive the technical vision for enterprise-grade AI solutions built on Microsofts agentic AI ecosystem.
You will lead the architecture and implementation of intelligent systems that integrate Microsoft Copilot Studio, Azure AI services, and the broader Microsoft 365 and Power Platform stack.
Your role will be instrumental in ensuring these solutions are scalable, secure, and compliant, while delivering measurable business value.
You will act as a trusted technical advisor and mentor, guiding development teams and stakeholders through the complexities of AI integration in hybrid and multi-cloud environments.
Your Profile
15+ years of experience in data and automation solution architecture using Microsoft technologies, with a proven successes in Generative and Agentic AI.
Proven track record in leading solution design for generative technologies, including effort estimation, pricing, and client-facing business case development.
Security: Understanding of security protocols, data encryption techniques, IAM policies, and other best practices related to AI systems on the cloud.
Optimization: Knowledge of techniques to enhance model performance, reduce latency, and optimize API calls.
Ability to work independently and as part of a team; ability to take initiative with minimal direction and to solve problems.
Excellent oral and written communication skills.
Flexibility-Multi-task adaptability.
Deep hands-on expertise with Microsoft Azure AI services, including Azure AI Foundry, Azure AI Agent Service, Microsoft Copilot Studio, and Semantic Kernel.Demonstrated leadership in designing scalable, secure, and compliant enterprise AI solutions.
Strong understanding of cloud design patterns, enterprise integration patterns, and responsible engineering practices.
Experience identifying opportunities for transformation, automation, and AI within enterprise environments.Working knowledge of cloud architectures (AWS, GCP, Azure), enterprise integration patterns, and DevOps practices.
Strong grasp of advanced AI concepts such as multi-agent workflows, reasoning and decision engines, and autonomous agent design.
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