SRE Engineer

Siemens Digital Industries Software; Maharashtra; Hybrid; INR 2,400,000 - 3,600,000; Full time

Benefits offered by this job

Competitive salary

Hybrid work model

Career growth opportunities

Job summary

Siemens Digital Industries Software is seeking an experienced DevOps/MLOps engineer to define, monitor, and enforce SLOs/SLIs for AI services and to ensure scalable, fault-tolerant infrastructure for model serving and data workflows.

You will manage Azure cloud resources with IaC tools (Terraform/ARM), oversee Kubernetes clusters (Docker, AKS), and build observability with Prometheus, Grafana, Datadog, and Open Telemetry, while leading incident response and RCA processes.

Qualifications

• Enforce SLOs/SLIs and error budgets for AI services.
• Lead incident response, RCA, and post-mortem processes to minimize downtime and recurrence.
• Proactively identify and resolve reliability risks before they impact end users.
• Maintain scalable, fault-tolerant infrastructure for data pipelines, ML workflows and data pipelines.
• Handle Azure cloud infrastructure using Terraform/ARM templates.
• Oversee Kubernetes clusters and containerized workloads (Docker) for AI microservices.
• Maintain observability stacks with Prometheus, Grafana, Datadog, or OpenTelemetry.
• Develop alerting systems to detect anomalies in AI model performance and latency.
• Automate operational tasks with scripting (Python, Bash, Go).
• Build and maintain CI/CD pipelines for model deployment and service updates.
• Implement MLOps practices to streamline deployment and monitoring of ML models.
• Ensure infrastructure aligns with security guidelines and regulatory standards.
• Collaborate with data engineers and data scientists to productionize AI systems.
• Foster a reliability-first culture across engineering teams.
• Contribute to on-call runbooks and playbooks.

Responsibilities

• Enforce SLOs, SLIs, and error budgets for AI services
• Lead incident response, 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

Skills

Problem-solving

Analytical thinking

Proactive issue resolution

Security awareness

Multi-tenant architecture

Cloud design

Education

Bachelor's degree in CS/IT

Tools

Azure AKS

Azure DevOps

Azure ARM

Terraform

Ansible

Jenkins

GitHub Actions

Prometheus

Grafana

Datadog

OpenTelemetry

Docker

Kubernetes

ELK Stack

Job description

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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