A
Senior AI Engineer - TX, NC
Apex Systems
3 hours ago
Full-time
On-site
Charlotte, North Carolina, United States
Software Engineer 4 – Senior AI Engineer (Microsoft Copilot Studio)
Client: Financial Services Location: Irving, TX – Preferred / Charlotte, NC Contract Length: 18 Months (Potential Extension or Conversion to FTE) Pay Rate: $65 - $70/hour (OT40) Top Requirements: 5+ years of Software Engineering experience with enterprise application and platform development. Deep hands-on expertise building AI Agents in Microsoft Copilot Studio. Strong experience with Microsoft 365 Copilot, Microsoft Graph, Teams, SharePoint, Outlook, and OneDrive integrations. Experience designing and implementing agent orchestration, multi-agent workflows, and enterprise AI solutions. Strong engineering background in workflow automation, reusable frameworks, enterprise integrations, and scalable solution design. Plusses: Experience with Azure AI Foundry. Experience implementing AI governance, observability, monitoring, and evaluation frameworks. Experience with CI/CD practices for AI solutions. Experience designing enterprise-wide AI standards, reusable agent frameworks, and prompt management strategies. Financial services or large enterprise technology experience. Job Summary: The Software Engineer 4 will serve as a Senior AI Engineer focused on designing, building, and scaling enterprise AI solutions using Microsoft Copilot Studio and Microsoft 365 Copilot. This role supports enterprise-wide AI engineering initiatives focused on agent development, workflow orchestration, automation, and Microsoft ecosystem integrations. The engineer will be responsible for creating intelligent agent-based solutions that leverage enterprise data, Microsoft Graph, and Microsoft 365 platforms to automate complex business processes and improve operational efficiency. The role requires deep technical expertise in Copilot Studio, strong architectural skills, and experience developing reusable AI frameworks and enterprise standards. Day-to-Day Responsibilities: Design and implement enterprise AI agents using Microsoft Copilot Studio and Microsoft 365 Copilot. Build multi-agent orchestration frameworks including task decomposition, workflow execution, validation, and recovery mechanisms. Develop declarative and custom AI agents supporting enterprise workflows. Create reusable agent templates, frameworks, and development standards. Develop enterprise integrations using Microsoft Graph across Teams, Outlook, SharePoint, OneDrive, and Microsoft 365 services. Design and deploy complex agentic workflows and tool invocation pipelines. Support AI solution governance, security, compliance, and responsible AI requirements. Build monitoring and observability solutions to measure agent performance, success metrics, reliability, and failure scenarios. Participate in architecture reviews, technical design sessions, and enterprise AI roadmap discussions. Collaborate with Product, Architecture, Engineering, and Platform teams to align solutions with strategic objectives. Optimize AI solutions for performance, scalability, latency, and operational efficiency. Contribute to AI engineering best practices including testing, prompt management, versioning, and CI/CD automation.
Client: Financial Services Location: Irving, TX – Preferred / Charlotte, NC Contract Length: 18 Months (Potential Extension or Conversion to FTE) Pay Rate: $65 - $70/hour (OT40) Top Requirements: 5+ years of Software Engineering experience with enterprise application and platform development. Deep hands-on expertise building AI Agents in Microsoft Copilot Studio. Strong experience with Microsoft 365 Copilot, Microsoft Graph, Teams, SharePoint, Outlook, and OneDrive integrations. Experience designing and implementing agent orchestration, multi-agent workflows, and enterprise AI solutions. Strong engineering background in workflow automation, reusable frameworks, enterprise integrations, and scalable solution design. Plusses: Experience with Azure AI Foundry. Experience implementing AI governance, observability, monitoring, and evaluation frameworks. Experience with CI/CD practices for AI solutions. Experience designing enterprise-wide AI standards, reusable agent frameworks, and prompt management strategies. Financial services or large enterprise technology experience. Job Summary: The Software Engineer 4 will serve as a Senior AI Engineer focused on designing, building, and scaling enterprise AI solutions using Microsoft Copilot Studio and Microsoft 365 Copilot. This role supports enterprise-wide AI engineering initiatives focused on agent development, workflow orchestration, automation, and Microsoft ecosystem integrations. The engineer will be responsible for creating intelligent agent-based solutions that leverage enterprise data, Microsoft Graph, and Microsoft 365 platforms to automate complex business processes and improve operational efficiency. The role requires deep technical expertise in Copilot Studio, strong architectural skills, and experience developing reusable AI frameworks and enterprise standards. Day-to-Day Responsibilities: Design and implement enterprise AI agents using Microsoft Copilot Studio and Microsoft 365 Copilot. Build multi-agent orchestration frameworks including task decomposition, workflow execution, validation, and recovery mechanisms. Develop declarative and custom AI agents supporting enterprise workflows. Create reusable agent templates, frameworks, and development standards. Develop enterprise integrations using Microsoft Graph across Teams, Outlook, SharePoint, OneDrive, and Microsoft 365 services. Design and deploy complex agentic workflows and tool invocation pipelines. Support AI solution governance, security, compliance, and responsible AI requirements. Build monitoring and observability solutions to measure agent performance, success metrics, reliability, and failure scenarios. Participate in architecture reviews, technical design sessions, and enterprise AI roadmap discussions. Collaborate with Product, Architecture, Engineering, and Platform teams to align solutions with strategic objectives. Optimize AI solutions for performance, scalability, latency, and operational efficiency. Contribute to AI engineering best practices including testing, prompt management, versioning, and CI/CD automation.