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AI-Native Software Developer

Yesterday 2026/11/18 ·Application closes in 118 days
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Job description

About Siemens Healthineers At Siemens Healthineers, we pioneer breakthroughs in healthcare. For everyone. Everywhere. Sustainably. Our purpose is to empower healthcare providers with innovative, reliable, and intelligent technologies that improve patient outcomes and make healthcare more accessible. By combining advanced medical devices, intelligent software, and modern engineering practices, we build solutions that address real-world healthcare challenges while ensuring sustainability and long-term impact. As AI transforms the way software is engineered and experienced, we are looking for AI-Native Software Developers who can leverage AI throughout the software development lifecycle while building secure, scalable, and intelligent healthcare applications. Role Overview As an AI-Native Software Developer, you will design, develop, and maintain high-quality software while effectively leveraging AI to accelerate engineering productivity and enhance software capabilities. You will integrate AI-powered services into applications, validate AI-generated outputs, and apply responsible AI principles to deliver reliable, secure, and scalable healthcare solutions. You will collaborate with cross-functional teams to deliver innovative products while continuously adopting emerging AI technologies and modern engineering practices. Key Responsibilities Analyze business and technical requirements and identify opportunities to incorporate AI capabilities where they add value. Design, develop, and maintain secure, scalable, and high-quality software solutions using modern engineering practices. Leverage AI-assisted engineering practices to improve productivity while validating AI-generated code, tests, and documentation. Integrate AI-powered features, services, or intelligent agents into applications using enterprise AI platforms and context engineering principles. Ensure software quality, reliability, and performance through automated testing, continuous delivery, and validation of AI-enabled features. Apply secure coding and responsible AI practices to ensure privacy, compliance, and trustworthy AI solutions. Collaborate across global teams and continuously adopt emerging technologies to drive engineering excellence. Qualifications Bachelor's or Master's degree in Computer Science / Software Engineering / Information Technology , or related discipline. 4–7 years of experience in software development using modern engineering practices. Strong understanding of software architecture, object-oriented design, and design patterns. Experience developing enterprise-scale cloud-native applications. Technical Skills Software Engineering C# , .NET / .NET Core REST APIs , Microservices Angular / React / JavaScript / TypeScript / HTML5 / CSS Cloud & DevOps Microsoft Azure (preferred) Docker / Kubernetes Azure DevOps , CI/CD pipelines Infrastructure as Code (desirable) AI Engineering Experience integrating AI services or Large Language Models into applications. Familiarity with AI-assisted software development tools (e.g., GitHub Copilot or equivalent). Understanding of context engineering principles for enterprise AI applications. Knowledge of Retrieval-Augmented Generation (RAG) concepts and AI orchestration frameworks is desirable. Familiarity with AI evaluation, guardrails, and responsible AI practices. Software Quality Test automation TDD / BDD Secure coding Performance optimization Observability and monitoring Behavioral Competencies Strong analytical and problem-solving skills. Growth mindset with passion for continuous learning. Ability to effectively collaborate across global teams. Strong communication and stakeholder management skills. Ability to balance engineering excellence with rapid innovation. Ownership mindset and commitment to delivering customer value. Preferred Qualifications Experience developing healthcare software or regulated products. Familiarity with medical device software standards and secure software development practices. Exposure to AI agents, workflow automation, or enterprise AI platforms. Contributions to open-source projects or developer communities are an advantage.
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