Roles and Responsibilities

• Lead the design and development of AI Agents using Microsoft Semantic Kernel, orchestrating prompts, skills, memory, and plugins
• Own containerization and deployment of services using Docker, including authoring secure, efficient multi-stage builds
• Build and maintain CI/CD pipelines (Azure DevOps, GitHub Actions) for automated testing and deployment
• Operate containerized workloads on Azure, leveraging AKS, ACI, Azure Functions, and App Services
• Integrate Azure AI services such as Azure OpenAI, Cognitive Search, Cosmos DB, and Azure SQL
• Implement observability using Application Insights, OpenTelemetry, Prometheus, and Grafana
• Ensure secure operations via Azure Key Vault, Managed Identities, and RBAC
• Collaborate with engineering teams to support RAG (retrieval-augmented generation) and integrate custom knowledge bases
• Drive technical best practices, mentoring teams on scalable architectures and cloud-native design patterns

Required Skills & Qualifications

• 7+ years of software engineering experience, including 3+ years leading complex, high-visibility projects
• Deep hands-on experience with Microsoft Semantic Kernel (for .NET 8+)
• Strong .NET engineering background
• Expertise in Azure services, including:
  • AKS, ACI, Azure App Service, Azure Functions
  • Azure OpenAI, Azure Cognitive Search, Cosmos DB, or Azure SQL
  • Advanced Docker and containerization skills, including image optimization and security scanning
  • Proficient in building CI/CD pipelines with Azure DevOps or GitHub Actions
• Demonstrated ability to instrument applications for observability with Application Insights, OpenTelemetry, and visual dashboards (e.g., Grafana)
• Strong background in RESTful APIs, microservices, and event-driven architecture
• Solid understanding of cloud security principles and governance using Azure Policy, Key Vault, and RBAC
• Excellent verbal and written communication skills with a track record of mentoring and leading teams

Preferred Experience

• Experience with vector and/or graph databases
• Background in retrieval-augmented generation (RAG) or custom embedding pipelines
• Working knowledge of Terraform for infrastructure as code
• Contributions to open-source projects, particularly in the Semantic Kernel ecosystem

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