Senior Technical Product Manager - Deployment & Platform Experience

We are Siemens 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. We are Siemens 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. Would you like to shape a deployment experience that makes complex technology simpler, more reliable and easier for customers to adopt? As our Senior Product Engineer (Deployment & Platform Experience), you'll work within the Product team and play a key role in shaping the deployment journey for Graph Studio and Lakehouse across cloud and customer-managed environments. Working collaboratively across Product Management, DevOps, Services, QA, Security and Engineering, you'll identify opportunities to remove deployment friction, define platform requirements and establish consistent operational workflows. Your work will help simplify customer onboarding, upgrades, troubleshooting, security integration and infrastructure automation. You'll bring your experience across Kubernetes, cloud infrastructure, authentication, deployment automation, observability and operational excellence, combining technical expertise with a strong understanding of the customer experience. You'll make a difference by: Shaping and driving the deployment experience roadmap for Graph Studio and Graph Lakehouse. Identifying opportunities to improve deployment across cloud, Kubernetes, authentication, networking, observability and security. Listening to feedback from Services teams and customers, translating insights into clear, prioritised roadmap requirements. Defining consistent deployment patterns for AWS, Azure, OpenShift and customer-managed Kubernetes environments. Developing requirements across Kubernetes deployments, Helm charts, Operators, container lifecycle management, high-availability configurations, persistent storage, service mesh, networking, load balancers and ingress controllers. Validating cloud-native deployment architectures across supported environments. Shaping requirements for Terraform and Infrastructure as Code, GitOps and CI/CD integration, environment provisioning and cluster onboarding. Partnering closely with Services teams to turn successful automation approaches into scalable operational patterns. Defining and validating requirements across Keycloak, OIDC and OAuth 2.0, SAML, RBAC, Kubernetes service accounts, Azure Managed Identity, AWS IAM and least-privilege deployment patterns. Driving requirements for centralised logging, Fluent Bit, OpenTelemetry, Amazon CloudWatch, Azure Monitor, operational dashboards, diagnostic tooling, sidecar containers and production troubleshooting workflows. Creating reference deployment architectures and defining supported deployment blueprints. Developing clear operational guidance that makes knowledge easier to share and reduces reliance on individual expertise. Your success is grounded in We're looking for someone who brings a strong foundation in cloud-native deployment and infrastructure automation, with experience in areas such as: Kubernetes, Docker, Helm charts and container technologies within production environments. Terraform and Infrastructure as Code principles. AWS and/or Azure cloud platforms and Linux administration. Identity and security management, including Keycloak, OIDC/OAuth 2.0, SAML, and cloud IAM. Designing and deploying enterprise-scale infrastructure automation and supporting operational excellence. Additional Experience That Would Be Valuable Consultancy Background. Knowledge graph platforms and semantic technologies. RDF and SPARQL. Enterprise SaaS deployments.