Design, develop, deploy, and operate enterprise AI solutions using Microsoft Copilot Studio, Microsoft Foundry, Azure AI, and enterprise data. Build copilots, agents, RAG pipelines, connectors, APIs, and secure integrations. Apply model evaluation, agent orchestration, authentication, ALM, CI/CD, monitoring, and responsible AI practices. Collaborate with customers to translate business needs into technical designs, troubleshoot solutions, and deliver production-ready architectures and documentation.
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.
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