SRE Engineer

Siemens; Pune District; On-site; INR 2,500,000 - 3,800,000; Full time

Job summary

Siemens Industry Software (India) Private Limited, headquartered in Pune, seeks an Experienced Professional to design and enforce SLOs/SLIs for AI services and lead incident response, RCA, and post-mortem processes. You will maintain scalable, cloud-native infrastructure and oversee AKS, Terraform, and CI/CD pipelines in a multi-tenant environment.

Responsibilities include building observability, automating tasks with Python/Bash, and ensuring security and regulatory compliance across data

Qualifications

• Bachelor’s degree in computer science, information technology, or a related field with 6-8 years of meaningful experience.
• Demonstrated experience supporting production-grade, high-availability systems
• Strong experience with Azure cloud services, including AKS, Azure DevOps, ARM, and monitoring tools.
• Proven expertise in handling multi-tenant, microservices-based architectures and deploying high-availability solutions.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform, Ansible, or ARM templates for handling and automating cloud resources.
• Hands-on experience with CI/CD tools (e.g., Jenkins, GitHub Actions, Azure DevOps/MLOps) and configuration management.
• Solid understanding of containerization technologies (Docker) and orchestration (Kubernetes).
• Secondary experience or familiarity with security practices, such as IAM, threat detection, and compliance standards.
• Solid understanding of secure supply chain practices, including management of code dependencies and open-source libraries.
• Strong problem-solving and analytical skills with a proactive approach to operational and security issues.

Responsibilities

• Enforce Service Level Objectives (SLOs), Service Level Indicators (SLIs), and Error Budgets for AI services
• Lead incident response, root cause analysis (RCA), and post-mortem processes to minimize downtime and prevent recurrence
• Proactively identify and resolve reliability risks before they impact end users
• Maintain scalable, fault-tolerant infrastructure for data pipelines, ML workflows and data workflows
• Handle cloud infrastructure (Azure) using Infrastructure as Code (IaC) tools such as Terraform
• Oversee Kubernetes clusters and containerized workloads (Docker) supporting AI microservices
• Maintain comprehensive observability stacks (metrics, logs, traces) using tools like Prometheus, Grafana, Datadog, or Open Telemetry
• Develop intelligent alerting systems to detect anomalies in AI model performance, latency, and efficiency
• Automate repetitive operational tasks through scripting and tooling (Python, Bash, Go)
• Build and maintain CI/CD pipelines for model deployment and service updates
• Implement MLOps practices to streamline the deployment and monitoring of ML models in production
• Ensure infrastructure and services align with security guidelines and relevant regulatory standards
• Partner with data engineers and data scientists to make AI systems production-ready
• Foster a reliability-first culture across engineering teams
• Contribute to on-call rotations and continuously improve on-call runbooks and playbooks

Education

Bachelor’s degree in computer science or information technology

Tools

Azure cloud services

Azure Kubernetes Service (AKS)

Azure DevOps

Azure Resource Manager (ARM)

Terraform

Ansible

ARM templates

Jenkins

GitHub Actions

Azure DevOps/MLOps

Docker

Kubernetes

Prometheus

Grafana

Datadog

Open Telemetry

Job description

Company

Siemens Industry Software (India) Private Limited

Organization

Digital Industries

Field of work

Research & Development

Experience level

Experienced Professional

Job type

Full-time

Work mode

Office/Site only

Employment type

Permanent

Location(s)

• Pune - Maharashtra - India

Siemens Digital Industries Software is a leading provider of solutions for the design, simulation, and manufacture of products across many different industries. Formula 1 cars, skyscrapers, ships, space exploration vehicles, and many of the objects we see in our daily lives are being conceived and manufactured using our Product Lifecycle Management (PLM) software.

Define, monitor, and enforce Service Level Objectives (SLOs), Service Level Indicators (SLIs), and Error Budgets for AI services, understand scalable, fault-tolerant infrastructure for AI model serving, training pipelines, and data workflows, maintain comprehensive observability stacks (metrics, logs, traces) using tools like Datadog or Open Telemetry.

Responsibilities:

Enforce Service Level Objectives (SLOs), Service Level Indicators (SLIs), and Error Budgets for AI services

Lead incident response, root cause analysis (RCA), and post-mortem processes to minimize downtime and prevent recurrence

Proactively identify and resolve reliability risks before they impact end users

Maintain scalable, fault-tolerant infrastructure for data pipelines, ML workflows and data workflows

Handle cloud infrastructure (Azure) using Infrastructure as Code (IaC) tools such as Terraform

Oversee Kubernetes clusters and containerized workloads (Docker) supporting AI microservices

Maintain comprehensive observability stacks (metrics, logs, traces) using tools like Prometheus, Grafana, Datadog, or Open Telemetry

Develop intelligent alerting systems to detect anomalies in AI model performance, latency, and efficiency

Automate repetitive operational tasks through scripting and tooling (Python, Bash, Go)

Build and maintain CI/CD pipelines for model deployment and service updates

Implement MLOps practices to streamline the deployment and monitoring of ML models in production

Ensure infrastructure and services align with security guidelines and relevant regulatory standards

Partner with data engineers and data scientists to make AI systems production-ready

Foster a reliability-first culture across engineering teams

Contribute to on-call rotations and continuously improve on-call runbooks and playbooks

Qualifications:

Bachelor’s degree in computer science, Information Technology, or a related field with 6-8 years of meaningful experience.

Demonstrated experience supporting production-grade, high-availability systems

Strong experience with Azure cloud services, including Azure Kubernetes Service (AKS), Azure DevOps, Azure Resource Manager (ARM), and monitoring tools.

Proven expertise in handling multi-tenant, microservices-based architectures and deploying high-availability solutions.

Proficiency in Infrastructure as Code (IaC) tools like Terraform, Ansible, or ARM templates for handling and automating cloud resources.

Hands-on experience with CI/CD tools (e.g., Jenkins, GitHub Actions, Azure DevOps/MLOps) and configuration management.

Solid understanding of containerization technologies (e.g., Docker) and orchestration (e.g., Kubernetes).

Secondary experience or familiarity with security practices, such as identity and access management (IAM), threat detection, and compliance standards.

Solid understanding of secure supply chain practices, including management of code dependencies and open-source libraries.

Strong problem-solving and analytical skills with a proactive approach to operational and security issues.

Preferred Skills:

Experience with supervising and logging tools (e.g., Prometheus, Grafana, ELK Stack) for proactive issue resolution.

Familiarity with zero-trust architecture principles

Knowledge of industry compliance standards such as SOC 2, ISO 27001, and GDPR, is a plus.

Experience with scripting and automation tools, such as Python, Bash, or PowerShell.

What We Offer:

Competitive salary and comprehensive benefits package.

Opportunities to work on ground breaking projects in cloud infrastructure and MLOps.

A collaborative, innovative work environment with room for career growth.

Why us?

Working at Siemens Software means flexibility - Choosing between working at home and the office at other times is the norm here. We offer great benefits and rewards, as you'd expect from a world leader in industrial software.

A collection of over 377,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we Work in. All employment decisions at Siemens are based on qualifications, merit, and business need. Bring your curiosity and creativity and help us shape tomorrow!

Siemens Software. Transform the Everyday

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