Job description:
We are seeking a Senior AI Agentic Solutions Engineer to design, develop, and deploy AI-powered solutions that enhance learning experiences, automate business processes, and improve workforce productivity. The role involves building intelligent agents, copilots, RAG solutions, and workflow automations using Microsoft Copilot Studio, Azure AI Foundry, Azure AI Services, and Google Gemini.
The ideal candidate will have hands-on experience developing agentic AI solutions integrated with LMS platforms, enterprise knowledge repositories, Microsoft 365, SharePoint, Teams, Power Platform, and other enterprise systems. Responsibilities include developing Azure Functions and APIs, creating custom connectors, implementing governance and monitoring frameworks, and collaborating with business and product teams to prototype, pilot, and scale AI-enabled solutions.
Experience
Required Skills
- Microsoft Copilot Studio
- Azure AI Foundry / Azure AI Services
- Google Gemini
- Agentic AI & Multi-Agent Systems
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering
- Azure Functions & Serverless Architecture
- API Development & Integration
- Microsoft 365, Teams, SharePoint
- Power Platform
- LMS Integrations (Workday Learning, SuccessFactors, Viva Learning, LinkedIn Learning)
- Enterprise Knowledge Management
- AI Governance & Monitoring
- Proof of Concept (POC) and Production Deployment Experience
Key Responsibilities
- Design and deploy AI agents and copilots using Microsoft Copilot Studio, Azure AI Foundry, and Google Gemini.
- Develop RAG solutions leveraging enterprise content and knowledge repositories.
- Build Azure Functions, APIs, and serverless services for AI orchestration and automation.
- Integrate AI solutions with Workday Learning, SuccessFactors, Viva Learning, LinkedIn Learning, and other learning platforms.
- Develop integrations with Microsoft 365, SharePoint, Teams, Power Platform, and enterprise applications.
- Establish prompt engineering standards, governance controls, evaluation frameworks, and monitoring practices.
- Support architecture design, POCs, pilots, and production deployments.
- Partner with product managers and business stakeholders to identify and deliver high-value AI use cases.