Job Overview

Microsoft is hiring a Consultant - Cloud Infra & AI for its Industry Solution - Global Center for Innovation and Delivery team. This full-time consulting opportunity is intended for experienced cloud infrastructure professionals who can combine Azure architecture, automation, AI infrastructure, networking, security, DevOps, and customer-facing delivery skills.

The role focuses on helping enterprise customers and partners design, implement, modernize, and optimize cloud and on-premises environments. You will work across infrastructure and application architecture rather than focusing on a single technology area. The position requires a practical consulting mindset, strong technical judgment, and the ability to translate business requirements into secure, scalable, and maintainable technology solutions.

As a Consultant - Cloud Infra & AI, you will contribute as an advisor, reviewer, technical specialist, or delivery resource on high-profile projects. You will help customers adopt Microsoft technologies effectively while identifying technical risks, improving solution quality, and developing repeatable approaches that can be applied across projects.

Key Responsibilities

• Design and optimize end-to-end Azure and on-premises infrastructure solutions for enterprise environments.
• Develop secure, scalable, resilient, and high-performing cloud architectures aligned with customer objectives.
• Provide technical quality assurance and identify, assess, and mitigate risks across customer and partner deliverables.
• Translate business requirements into practical cloud, infrastructure, networking, security, and AI solutions.
• Help customers adopt Microsoft technologies through architecture guidance, technical workshops, envisioning sessions, and solution design engagements.
• Develop reusable automation and infrastructure patterns using Infrastructure as Code and DevOps practices.
• Design Azure Landing Zones and cloud environments using Microsoft Cloud Adoption Framework principles.
• Support large-scale migration and modernization initiatives involving Azure, AWS, and GCP environments.
• Implement secure cloud connectivity, network segmentation, governance controls, and Zero Trust practices.
• Explore emerging AI and data technologies and incorporate suitable capabilities into customer infrastructure solutions.
• Identify opportunities to reuse intellectual property, technical assets, and community resources to improve project consistency and delivery predictability.
• Collaborate with technical and business stakeholders to ensure solutions remain aligned with customer priorities.

Required Skills

Candidates should have 4 to 8 years of industry experience, including at least 4 years of hands-on Azure Infrastructure experience. Strong knowledge of Azure architecture, infrastructure services, networking, security, automation, and DevOps is essential.

The role requires practical experience across Azure IaaS and PaaS services covering compute, storage, and networking. Candidates should understand Azure Virtual Network, ExpressRoute, virtual WAN, ingress and egress patterns, Network Virtual Appliances, and secure connectivity across hybrid environments.

Strong Infrastructure as Code experience is expected. You should be comfortable with Terraform and at least one of Microsoft's infrastructure automation technologies such as ARM templates, Bicep, PowerShell, or Azure CLI. Modular and reusable infrastructure deployment practices are particularly relevant.

Experience with Azure DevOps and YAML-based pipelines is required. Familiarity with GitHub, GitLab, or Jenkins for CI/CD is also valuable.

Preferred Skills

Experience with cloud migration from AWS or GCP to Azure is highly relevant. Candidates should understand migration activities from assessment and planning through execution, optimization, container migration, and modernization.

Knowledge of Microsoft Cloud Adoption Framework and Well-Architected Framework principles is important for designing governed and resilient cloud environments. Experience with Azure Migrate and enterprise-scale migration programs can strengthen an application.

Security experience is also valuable, particularly with Azure Firewall, Network Security Groups, Private Link, VPN and ExpressRoute security, network segmentation, Azure Policy, governance controls, and Zero Trust architecture.

AI-related experience is another important part of the role. Candidates should understand cloud-based AI and machine learning workloads and have practical exposure to Azure AI services or AI development tooling.

Education

A Bachelor's degree in Computer Science, Engineering, or an equivalent professional background is required. Advanced technical certifications or higher education are preferred. AZ-104 Microsoft Azure Administrator certification is mandatory, while AZ-305 Azure Solutions Architect Expert is highly preferred. Terraform Associate certification is strongly valued, and AI-900 or an equivalent cloud AI certification is an advantage.

Experience

The expected experience range is 4 to 8 years, with a minimum of 4 years focused on Azure Infrastructure. Candidates should have experience delivering customer-facing technology projects in large enterprise environments and working across application architecture and cloud infrastructure.

Practical consulting experience is important. Applicants should be able to demonstrate participation in architecture discussions, technical workshops, solution design sessions, cloud adoption programs, migration initiatives, or infrastructure modernization projects.

Required Technologies

• Microsoft Azure
• Azure IaaS
• Azure PaaS
• Azure Landing Zones
• Azure Virtual Network (VNet)
• ExpressRoute
• Azure Virtual WAN (vWAN)
• Network Virtual Appliances (NVAs)
• Azure Firewall
• Network Security Groups (NSGs)
• Azure Private Link
• VPN
• Azure Policy
• Microsoft Cloud Adoption Framework (CAF)
• Well-Architected Framework (WAF)
• Azure DevOps
• YAML pipelines
• GitHub
• GitLab
• Jenkins
• Terraform
• ARM Templates
• Bicep
• PowerShell
• Azure CLI
• Azure Migrate
• AWS
• GCP
• Python
• Azure AI Services
• Azure AI Foundry
• Azure AI Search
• AI Agent Services
• Visual Studio
• GitHub Copilot
• OpenAI models
• Infrastructure as Code (IaC)
• CI/CD
• Kubernetes
• Containerization

Soft Skills

This consulting position requires clear communication and strong stakeholder management. You should be comfortable presenting technical recommendations to both technical and non-technical audiences and explaining complex architecture decisions in practical business terms.

Curiosity and continuous learning are important because the role covers evolving cloud and AI technologies. The ideal candidate is adaptable, receptive to feedback, willing to expand technical ownership, and interested in earning relevant certifications.

Strong collaboration, mentoring, knowledge sharing, problem solving, and customer focus are also important. Experience working in Agile or Scrum environments can help candidates adapt to project delivery expectations.

Benefits of Working in this Role

This role offers exposure to enterprise-scale cloud consulting, Azure architecture, infrastructure automation, security, DevOps, cloud migration, AI workloads, and customer transformation projects. The broad technical scope can help experienced infrastructure professionals strengthen both architecture and consulting capabilities.

Working across different customer requirements and industries can also provide opportunities to develop solution design, presentation, stakeholder management, technical leadership, and reusable engineering practices. The position is particularly relevant for professionals who want to combine hands-on cloud expertise with strategic consulting and customer delivery.

Work Mode

The position is full-time and follows a hybrid working arrangement with an expectation of working from the office three days per week. Travel is expected to be less than 25%.

Location

The primary listed location is Hyderabad, Telangana, India. The job posting also indicates two additional locations, but their names are not specified in the provided job description.

Who Should Apply

This opportunity is suitable for experienced Azure infrastructure consultants, cloud architects, DevOps professionals, infrastructure engineers, and technology consultants who have worked on enterprise-scale environments.

Candidates with strong Azure architecture experience, Infrastructure as Code skills, cloud migration knowledge, networking expertise, security experience, and customer-facing delivery backgrounds should consider applying. Professionals who can connect infrastructure engineering with AI workloads and modern cloud services may be especially relevant.

Career Growth

The role can help experienced cloud professionals expand into broader solution architecture and consulting responsibilities. Exposure to customer strategy, technical workshops, enterprise migration, AI infrastructure, security, governance, and cross-industry projects can build a wider professional skill set.

Continued involvement with Azure certifications, emerging AI services, automation, and reusable architecture patterns can also support long-term growth toward senior consulting, cloud architecture, and technical leadership opportunities.

Application Advice

Applicants should clearly present their Azure Infrastructure experience and identify the projects where they designed, deployed, migrated, secured, or optimized cloud environments. Highlight hands-on work with Azure Landing Zones, networking, Terraform, Bicep, ARM templates, Azure DevOps, CI/CD, and automation.

If you have worked on AWS or GCP to Azure migrations, describe the scope and your contribution to assessment, planning, implementation, modernization, or optimization. Include relevant security and governance experience, especially Zero Trust, Azure Policy, Azure Firewall, Private Link, NSGs, and secure hybrid connectivity.

Candidates should also list their Azure certifications accurately and highlight customer-facing consulting experience. For AI-focused work, mention practical exposure to Azure AI Services, AI Foundry, AI Search, AI agents, OpenAI models, Python automation, or AI development tools where applicable. Avoid listing technologies without being prepared to discuss real project experience.