AI Platform Architect

Siemens Energy, Inc.; Gurugram District; Hybrid; INR 4.000.000 - 6.000.000; Vollzeit

Benefits dieser Stelle

Remote Working up to 2 days per week

Global team exposure

Opportunities to work on innovative AI

Medical benefits

Paid holidays and parental leave

Learn@Siemens-Energy platform

Zusammenfassung

Siemens Energy is seeking an experienced AI Platform Architect to design, evaluate, and lead the rollout of enterprise-scale AI platforms across AWS, Azure, and GCP. You will define platform strategy, guide architecture decisions, and enable 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.

Qualifikationen

• 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.

Aufgaben

• 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.

Kenntnisse

AI platform design

Multi-cloud architecture

Terraform

Kubernetes

Docker

GitOps

Python

Scripting (PowerShell,Bash)

Security governance

Observability & monitoring

Tools

AWS

Azure

GCP

GitHub

GitLab

Azure DevOps

Jenkins

Docker

Kubernetes

Helm

GitOps

Jobbeschreibung

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.

About The Team

Who is Siemens Energy?

Siemens Energy

At Siemens Energy, we are more than just an energy technology company. With ~100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation.

Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.

Find out how you can make a difference at Siemens Energy: https://www.siemens-energy.com/employeevideo

Our Commitment to Diversity

Lucky for us, we are not all the same. Through diversity we generate power. We run on inclusion and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character – no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences.

Rewards / Benefits

• Employees are eligible for Remote Working arrangements up to 2 days per week.
• Opportunities to work with a global team.
• Opportunities to work on and lead a variety of innovative projects.
• Medical benefits.
• Time off, paid holidays, and parental leave.
• Continual learning through the Learn@Siemens-Energy platform.

https://jobs.siemens-energy.com/jobs