Products & Solutions Development Team Leader

Job Requirements Engineering Manager – Digital Backbone Role purpose: Build the teams, engineering system, and leadership capability that turn Digital Backbone into the reusable, trusted foundation for Siemens Healthineers’ next generations of connected, cloud-ready, AI-enabled healthcare products. The role combines people leadership, product-minded engineering management, and cross-organization influence to convert platform strategy into measurable customer, business, and engineering outcomes. What Digital Backbone Is Digital Backbone is the common digital and engineering foundation that connects products, services, data, devices, and clinical workflows across Digital & Automation. It provides reusable platform capabilities for cloud, edge, and on-premises deployments so business lines can innovate faster without repeatedly rebuilding infrastructure, integration, deployment, data, fleet, licensing, observability, and workflow capabilities. Its value is not measured only by platform delivery, but by the speed, quality, reuse, interoperability, and new business outcomes it enables across the Siemens Healthineers ecosystem. What Digital Backbone Must Enable in the Coming Years · One engineering foundation across deployment models: enable containerized components and consistent development, integration, release, and operation across cloud, edge, and on-premises environments. · Reusable platform products at enterprise scale: shift from local solutions to governed capabilities that multiple business lines can discover, adopt, integrate, and evolve. · Connected and interoperable healthcare ecosystems: strengthen common services for clinical information exchange, workflow orchestration, fleet and device connectivity, deployment, data, analytics, licensing, and business operations. · AI-ready and AI-native healthcare engineering: provide safe, auditable foundations for AI-enabled workflows while embedding responsible AI into the software lifecycle, engineering knowledge, quality, and productivity. · Faster customer value and new business models: shorten time-to-market, decouple software development from delivery, expand fleet-wide services, and enable subscription, metering, marketplace, and data-driven offerings. · Operational trust at scale: make reliability, cybersecurity, privacy, regulatory evidence, observability, supportability, and lifecycle sustainability intrinsic platform qualities. · A product-oriented global operating model: create clear end-to-end ownership, transparent priorities, strong domain leadership, and accountable collaboration across product, engineering, architecture, quality, and business stakeholders. Engineering Manager Mission Create an environment in which autonomous, inclusive, high-performing teams deliver dependable platform products and continuously increase their impact across Digital & Automation. The Engineering Manager owns the health and capability of the engineering organization: the right people, skills, ways of working, quality discipline, delivery system, and partnerships needed to scale Digital Backbone outcomes. Core Accountabilities · Translate strategy into team outcomes: connect Siemens Healthineers, Digital & Automation, BTT, platform, and product priorities to clear team objectives, roadmaps, technical investments, and measurable outcomes. · Own organizational capability: build balanced teams, identify future skill needs, develop succession, grow technical and people leaders, and enable mobility across products, domains, and geographies. · Lead predictable value delivery: establish outcome-based planning, dependency and risk management, transparent flow metrics, and effective collaboration across teams without reducing agility to ceremony compliance. · Drive engineering excellence: improve architecture realization, software craftsmanship, automation, CI/CD, test strategy, cybersecurity, reliability, observability, maintainability, and lifecycle cost. · Scale platform adoption and reuse: treat internal consumers as customers, reduce onboarding friction, actively manage feedback, avoid duplicate solutions, and make reusable capabilities the preferred path. · Lead responsible AI transformation: model effective AI use, establish human validation and governance, develop AI-native skills, and convert successful experiments into reusable engineering practices and product value. · Manage end-to-end ownership: ensure teams understand and own build, release, operation, support, quality, and improvement of their platform products throughout the lifecycle. · Shape cross-functional decisions: partner with Product Managers, Architects, System Engineers, Quality, Cybersecurity, Operations, and business lines to resolve trade-offs and align investment with enterprise value. · Build a trusted culture: create psychological safety, high standards, inclusion, accountability, candid feedback, and space for experimentation and learning. Promote and protect Peakon participation and leverage it as strategic tool for employee engagement. · Represent engineering: communicate progress, risks, options, and impact in business language; influence priorities and secure the decisions, funding, and staffing needed for sustainable outcomes. Role Boundaries and Key Partnerships The Engineering Manager is accountable for people, engineering capability, delivery health, and the environment in which technical decisions are executed. Product Managers own product value, priorities, and market outcomes; Architects own architectural direction and integrity; technical leaders guide implementation and engineering practices. The Engineering Manager connects these accountabilities, makes ownership explicit, removes systemic barriers, and ensures decisions become dependable outcomes rather than parallel plans. Measures of Success · Accountability: the degree to which the engineering manager can create accountability amongst developers and team leadership acting as the anchor for stability and transparency. · Customer and ecosystem impact: adoption, active consumers, integration lead time, reuse, customer outcomes, and satisfaction of internal and external partners. · Delivery performance: predictable commitments, shorter lead time, improved flow, controlled dependencies, and faster recovery from issues. · Engineering quality: automation, defect escape rate, reliability, security posture, observability, maintainability, and reduced technical debt or lifecycle cost. · AI and modernization impact: measured productivity and quality gains, reusable AI-enabled workflows, responsible adoption, and migration from legacy approaches. · People and capability: critical-skill coverage, internal growth, leadership pipeline, engagement, inclusion, retention, and evidence-based development. · Business contribution: avoided duplication, lower cost to serve, faster time-to-market, platform-enabled revenue opportunities, and progress against strategic targets. What Makes This Role Exciting This is an opportunity to shape how future healthcare software is built and delivered—not only to manage an existing team. The Engineering Manager will help create the foundation on which connected devices, interoperable clinical workflows, AI-enabled solutions, fleet services, and future software-defined products can scale. The role offers influence across business lines and geographies, combines people leadership with technology transformation, and turns engineering excellence into visible customer and business impact.