01Overview
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.
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
Bachelors 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.
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.
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.
Experience with supervising and logging tools (e.g., Experience with scripting and automation tools, such as Python, Bash, or PowerShell.
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.
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. Bring your curiosity and creativity and help us shape tomorrow!
Siemens Software. LI-Hybrid
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