AI Platform Architect

AI Platform Architect

About the Role

Location India Haryana Gurugram Company Siemens Energy Industrial Turbomachinery India Private Limited Organization EVP Global Functions Business Unit Digital Core Full / Part time Full-time Experience Level Experienced Professional

A Snapshot of Your Day

As an AI Platform Architect, you will design, evaluate, and lead the rollout of enterprise-scale AI platforms, including Generative AI, Agentic AI, orchestration layers, and shared AI services across a multi-cloud environment. Your day will involve defining platform strategy, guiding architecture decisions, and enabling scalable adoption of AI solutions across business units. You will work at the intersection of AI architecture, cloud platform engineering, and enterprise enablement, ensuring reliable, secure, and high-performing AI platforms.

How You’ll Make an Impact

• Define and own enterprise AI platform architecture covering Generative AI, Agentic AI, orchestration layers, model serving, and shared AI services.
• Design scalable, secure, and reusable AI platforms across AWS, Azure, and GCP.
• Establish architectural standards for AI lifecycle management, observability, security, and governance.
• Evaluate Agentic AI platforms, frameworks, and orchestration tools, including multi-agent systems.
• Define reference architectures for agent-based workflows and AI-driven automation.
• Lead enterprise setup, onboarding, and rollout of Agentic AI platforms.
• Enable adoption through reusable patterns, best practices, and governance models.
• Collaborate with business and engineering teams to scale AI use cases from proof-of-concept to production.
• Architect and govern cloud-native AI infrastructure, including Kubernetes platforms (EKS, AKS, GKE) and GPU-based compute.
• Implement CI/CD pipelines and Infrastructure-as-Code practices using tools such as Terraform and GitOps.
• Ensure platform reliability, performance, and cost efficiency.
• Implement observability, monitoring, and operational excellence practices.
• Ensure alignment with enterprise security, compliance, and AI governance requirements.
• Define controls for data access, model usage, auditability, and risk management.
• Drive standardization across platforms, tools, and delivery frameworks.

What You Bring

• 8–10+ years of experience in AI platforms, cloud architecture, or platform engineering.
• Proven expertise in multi-cloud architecture and platform scaling.
• Strong experience with cloud platforms including AWS, Azure, and GCP.
• Hands-on experience with DevOps tools such as Terraform, GitHub/GitLab/Azure DevOps, Jenkins, Docker, Kubernetes, Helm, and GitOps.
• Proficiency in programming and scripting languages including Python, Bash, PowerShell, and YAML.
• Experience with Kubernetes platforms such as EKS, AKS, and GKE.
• Expertise in observability, monitoring, and automated deployment frameworks.
• Experience with AI platform components such as Agentic AI frameworks, orchestration layers, model serving, and AI workflows.
• Strong understanding of security compliance, AI governance, risk assessments, and operational controls.
• Hands-on exposure to Agentic AI or orchestration frameworks is an advantage.