Cloud & AI Platform Specialist - Azure

Lead Azure discovery, advisory and architecture engagements, translating customer objectives into secure and practical platform designs.

Design and implement Azure platform foundations, including landing zones, identity, networking, governance, policy, security controls and self-service capabilities.

Build repeatable automation using Infrastructure as Code, GitOps, policy as code and continuous integration and delivery practices.

Design and deploy AI-ready environments using services such as Azure AI Foundry, Azure OpenAI and Azure AI Search, including retrieval-augmented generation, vector search and secure data integration patterns.

Develop and support governed agentic workflows, including tool integrations, human oversight, lifecycle controls, testing, monitoring and cost management.

Establish responsible AI practices, including model and agent governance, data and prompt controls, security guardrails, consumption management and operational accountability.

Enable engineering teams through GitHub Enterprise, GitHub Actions, GitHub Advanced Security, GitHub Copilot and secure, AI-assisted software delivery practices.

Establish observability and reliability practices across cloud platforms, applications, AI services and agentic workflows, including telemetry, dashboards, service objectives, runbooks and automated remediation.

Contribute reusable architectures, automation, tools and delivery patterns that strengthen cloud and AI platform capability.

Support solution shaping, estimates, proposals, risk assessments and customer presentations, communicating effectively with technical and executive stakeholders.

Proven experience in Azure consulting, cloud architecture and customer-facing technology delivery.

Strong hands-on capability in cloud platform engineering, infrastructure automation and Infrastructure as Code using technologies such as Terraform or Bicep.

Strong knowledge of secure-by-design cloud foundations, including identity, networking, governance, policy, security and operational controls.

Demonstrated experience designing, implementing or supporting AI platforms and AI-enabled solutions in an enterprise environment.

Practical experience with Azure AI services such as Azure AI Foundry, Azure OpenAI or Azure AI Search, or comparable enterprise AI platform technologies.

Strong understanding of AI solution patterns, including retrieval-augmented generation, vector search, secure data integration, model access controls and responsible AI governance.

Experience designing or supporting agentic workflows, AI automation, tool integrations or AI-powered business processes.

Understanding of the security, governance, testing, observability, lifecycle and cost considerations associated with enterprise AI and agentic solutions.

Practical knowledge of modern developer tooling and delivery practices, including APIs, containers, test automation, CI/CD, GitOps and secure software development.

Fluency in one or more modern development languages, such as Python, TypeScript, C#, Java, Go or Rust, with the ability to design, interpret and contribute to code-based solutions.

Strong communication and stakeholder engagement skills, including the ability to explain complex platform and AI decisions and their business value to technical and executive audiences.

Commercial awareness and experience contributing to workshops, solution shaping, estimates, proposals or technical risk assessments.

Advanced AI engineering or enterprise-scale AI application development.

Experience with AI gateways, model observability, Model Context Protocol or comparable tool integration patterns.

Kubernetes platform engineering, FinOps or advanced security architecture.

Product development, software-as-a-service design or managed service transition experience.

Relevant Azure, AI, GitHub or Terraform certifications.

Experience mentoring others, contributing to technical communities or owning reference architectures.