AI Agent Developer

Position: AI Agent Developer

Location: Upper Gwynedd, PA***Hybrid***

Duration: 1 Years

Expert AI Agent Developer - Learning Technologies & Intelligent Automation

Key Responsibilities

Design, develop, and deploy intelligent agents and copilots using Microsoft Copilot Studio, Azure AI Foundry, and Google Gemini.

• Build agent-driven experiences that support learning discovery, skills development, knowledge retrieval, content recommendations, and employee enablement.
• Develop Azure Functions, APIs, and serverless services to support agent orchestration, integrations, and automation workflows.
• Create Retrieval-Augmented Generation (RAG) solutions leveraging enterprise content repositories and learning platforms.
• Integrate AI solutions with learning technologies such as Workday Learning, SuccessFactors, Viva Learning, LinkedIn Learning, and other content providers.
• Develop custom connectors and integrations with applications like - Microsoft 365, SharePoint, Teams, Power Platform, and our other enterprise systems.
• Collaborate with product managers and business stakeholders to identify high-value AI use cases and translate requirements into scalable solutions.
• Establish prompt libraries, agent instructions, evaluation frameworks, governance controls, and monitoring practices.
• Support technical architecture, proof-of-concept development, pilot programs, and production deployments.
• Stay current on emerging capabilities across Microsoft Copilot, Azure AI, Gemini, and agentic AI frameworks.

Skill Requirements

Required Qualifications

5+ years of software development, solution architecture, or platform engineering experience.

• Proven experience developing applications using Microsoft Copilot Studio and Azure AI Services.
• Strong hands-on development skills in:

o Python

• JavaScript/TypeScript
• Azure Functions
• REST APIs
• Microsoft Graph API
• Experience developing solutions using Google Gemini APIs and agent frameworks.
• Experience designing RAG architectures using vector databases, embeddings, and enterprise knowledge repositories.
• Experience integrating enterprise SaaS platforms and learning systems.
• Strong understanding of prompt engineering, agent orchestration, tool calling, memory, grounding, and evaluation methodologies.
• Experience working within enterprise security, compliance, and governance requirements.
• Excellent communication and stakeholder management skills.