.NET enterprise architecture (Agentic AI) - Enterprise Solutions

As an experienced AI Architect with a strong foundation in .NET enterprise architecture and hands-on capability in Python and Agentic AI systems, your role will be crucial in leading the architecture and technical direction for building cloud-native, scalable, secure, and observable AI solutions on Microsoft Azure. Here is a summary of your role: Key Responsibilities: - Solution Architecture & System Design: - Architect and design cloud-native solutions using .NET and microservices architecture with modern integration patterns. - Lead architecture reviews ensuring consistency with scalability, resiliency, performance, and maintainability principles. - Azure Engineering & Platform Enablement: - Design and guide implementation using Azure App Services and broader Azure platform services. - Ensure cloud architecture covers security, identity, networking, governance, and operational excellence. - DevOps, CI/CD & Infrastructure as Code: - Partner with DevOps/Platform teams to implement and optimize CI/CD pipelines, deployment strategies, and environment automation. - Drive Infrastructure as Code (IaC) using Terraform templates for repeatable and compliant deployments. - Integration, APIs & Enterprise Connectivity: - Own the approach for system integration, API strategy, and service contracts across internal/external systems. - Ensure robust patterns for API reliability, versioning, backward compatibility, and integration resilience. - Observability, Reliability & Quality: - Define observability standards for distributed systems. - Drive reliability practices across microservices and AI components. - Exposure to AI / Agentic Architecture: - Define and drive end-to-end architecture for Agentic AI solutions. - Establish architectural standards for prompting strategy, agent memory/context handling, and evaluation approach. - Technical Leadership: - Mentor engineers and guide best practices. - Collaborate with product, engineering, and stakeholders to align architecture with roadmap and delivery milestones. Required Qualifications: - 10+ years overall experience in software engineering/architecture with a strong enterprise .NET background. - Experience designing or implementing Agentic AI systems. - Strong experience with Azure App Services and cloud-native design. - Strong experience in CI/CD and Infrastructure as Code using Terraform. - Proven expertise in microservices architecture and system integration. About UST: UST is a global digital transformation solutions provider. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients organizations. With over 30,000 employees in 30 countries, UST builds for boundless impacttouching billions of lives in the process. As an experienced AI Architect with a strong foundation in .NET enterprise architecture and hands-on capability in Python and Agentic AI systems, your role will be crucial in leading the architecture and technical direction for building cloud-native, scalable, secure, and observable AI solutions on Microsoft Azure. Here is a summary of your role: Key Responsibilities: - Solution Architecture & System Design: - Architect and design cloud-native solutions using .NET and microservices architecture with modern integration patterns. - Lead architecture reviews ensuring consistency with scalability, resiliency, performance, and maintainability principles. - Azure Engineering & Platform Enablement: - Design and guide implementation using Azure App Services and broader Azure platform services. - Ensure cloud architecture covers security, identity, networking, governance, and operational excellence. - DevOps, CI/CD & Infrastructure as Code: - Partner with DevOps/Platform teams to implement and optimize CI/CD pipelines, deployment strategies, and environment automation. - Drive Infrastructure as Code (IaC) using Terraform templates for repeatable and compliant deployments. - Integration, APIs & Enterprise Connectivity: - Own the approach for system integration, API strategy, and service contracts across internal/external systems. - Ensure robust patterns for API reliability, versioning, backward compatibility, and integration resilience. - Observability, Reliability & Quality: - Define observability standards for distributed systems. - Drive reliability practices across microservices and AI components. - Exposure to AI / Agentic Architecture: - Define and drive end-to-end architecture for Agentic AI solutions. - Establish architectural standards for prompting strategy, agent memory/context handling, and evaluation approach. - Technical Leadership: - Mentor engineers and guide best practices. - Collaborate with product, engineering, and stakeholders to align architecture with roadmap and delivery milestones. Required Qualifications: - 10+ years overall experience in software engineering/architecture with a strong enterprise .NET background. -