The ideal candidate combines strong software engineering fundamentals with hands-on experience in AI application development, orchestration, API integration, and enterprise operations. This role will help establish patterns for how AI agents are built, governed, observed, and continuously improved in production. Success in this position requires the ability to balance innovation with operational rigor, including security, compliance, resilience, observability, human-in-the-loop controls, and lifecycle management for AI-driven capabilities. The Agentic AI Engineer will also document designs and procedures, support testing and rollout activities, and collaborate across teams to remove delivery barriers and ensure solutions align with enterprise standards.
Key Responsibilities
Engineer production-ready solutions with strong observability, traceability, evaluation, resiliency, and governance to support enterprise-scale deployment and ongoing optimization.
Develop and maintain APIs, connectors, orchestration components, and automation services required to connect AI agents with operational systems and workflows.
Desired Qualifications
Experience integrating applications with enterprise platforms and APIs such as Microsoft Graph, Teams, ServiceNow, monitoring tools, security platforms, infrastructure services, cloud services, and operational data sources.
Experience with DevOps, CI/CD pipelines, Git-based workflows, automated testing, and infrastructure-as-code in enterprise cloud environments with Azure DevOps and Bicep or equivalent
.
Preferred Certifications
Microsoft certifications related to Azure, AI, data, security, or development (for example: AZ-900, AZ-500, AZ-204, AZ-400, AI-901, AI-102, AI-103, AI-200).
Cloud, networking, security, or automation certifications from Microsoft, AWS, CompTIA, Cisco, or similar providers are beneficial.
