AI Engineer - Copilot & Foundry

Responsibilities

• Design, build, test, deploy, and operate enterprise AI solutions using Microsoft Copilot Studio and Microsoft Foundry.
• Develop customer-facing copilots, agents, and generative AI applications using low-code and pro-code approaches.
• Design agent architectures that combine Microsoft 365 Copilot, Copilot Studio, Microsoft Foundry, Azure AI services, and enterprise data sources.
• Build and implement agentic solutions using RAG, MCP, Agent orchestration, and tool calling / function calling frameworks .
• Develop custom connectors, plugins, tools, APIs, and integrations that enable agents to securely interact with business systems and data.
• Select, evaluate, and orchestrate models based on use case, quality, performance, security, and cost considerations.
• Implement secure authentication, authorization, identity, data access, and service-to-service integration patterns for AI solutions.
• Apply Application Lifecycle Management (ALM) practices, including source control, environment strategy, automated testing, CI/CD, deployment, monitoring, and ongoing iteration.
• Collaborate directly with customers to discover requirements, translate business needs into technical designs, and deliver production-ready solutions.
• Troubleshoot and optimize copilots, agents, prompts, models, and retrieval pipelines for accuracy, reliability, latency, and maintainability.
• Document solution architectures, technical designs, deployment procedures, security considerations, and operational guidance as part of customer deliverables.

Required Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, or a related technical field.
• 3+ years of experience in software engineering, application development, cloud engineering, AI engineering, or automation-focused roles.
• Hands-on experience building AI-powered applications, copilots, or agents using Microsoft Copilot Studio, Microsoft Foundry, Azure AI services, or comparable platforms.
• Proficiency with at least one modern programming language, such as Python, C#, TypeScript, or JavaScript.
• Experience designing and consuming REST APIs, custom connectors, plugins, tools, or event-driven integrations.
• Working knowledge of generative AI concepts and architectures, including prompt engineering, model inference, orchestration, agent design patterns, and grounding.
• Experience designing or implementing RAG solutions using enterprise content, search, vector databases, or retrieval pipelines.
• Solid understanding of Microsoft Entra ID, authentication, authorization, application permissions, managed identities, and secure API design.
• Experience applying engineering and ALM practices including Git, testing, CI/CD, environment promotion, monitoring, and technical documentation.
• Strong problem-solving and communication skills, with the ability to work directly with customers and cross-functional delivery teams.
  
  

Desired Qualifications

• Relevant Microsoft certifications in Azure AI, Azure development, Power Platform, Copilot Studio, or related Microsoft technologies.
• Experience implementing solutions with Microsoft 365 Copilot, Copilot Studio, Microsoft Foundry, Azure AI Search, Azure OpenAI, or Microsoft Graph.
• Experience building multi-agent or multi-model solutions and evaluating model quality, latency, and cost.
• Familiarity with Model Context Protocol (MCP), agent runtimes, tool calling, or equivalent agent integration patterns.
• Experience integrating AI solutions with Microsoft 365, Dataverse, SharePoint, Dynamics 365, or other enterprise applications and data sources.
• Familiarity with AI governance, responsible AI, data security, content safety, observability, and evaluation practices.
• Experience with cloud infrastructure, containers, serverless services, infrastructure as code, or distributed systems.
• Consulting or professional services experience delivering customer-specific solutions in enterprise or regulated environments.
• Experience collaborating with security, data, compliance, adoption, and change management teams during solution delivery.
• Demonstrated commitment to staying current with rapidly evolving Microsoft AI platforms, development practices, and responsible AI guidance.