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# AI & Data Innovation Engineer

- **Company:** Siemens AG
- **Location:** München, Germany
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Information Engineering, Python (Programming Language), Software Architecture, Mendix, Software Engineering, Data Streaming, Snowflake, Generative AI, Agentic-AI, Information Technology, Low-code, Software Version Control, Devsecops
- **Published:** November 11, 2026
- **Apply:** https://jobs.siemens.com/en_US/externaljobs/ApplicationMethods?folderId=529122

## About the Role

* Strong analytical and problem-solving skills, a can-do mindset and the ability to quickly understand unfamiliar assurance processes, practitioner needs and business contexts, and translate them into meaningful opportunities and solutions
 * A master's degree in computer science, business informatics, data science, engineering or a comparable field.
 * At least 5+ years of hands-on experience in software development, data engineering, analytics or AI engineering, ideally in an enterprise environment.
 * Strong expertise in several relevant technologies, such as Python, Azure cloud &AI stack, Snowflake, Mendix or comparable platforms.
 * Practical experience building and introducing GenAI applications, AI agents or agentic workflows.
 * A sound understanding of software architecture, data models, testing, version control, DevSecOps and lifecycle management.
 * A strong ownership mind set and confidence working directly with auditors and other assurance practitioners, and communicating technical options, decisions and trade-offs clearly to Product Owners and management.
 * Experience with audit, risk, controls or comparable assurance processes is an advantage. Alternatively, you can demonstrate strong process expertise and the ability to build assurance knowledge quickly.
 * Curiosity, ownership and a strong willingness to learn in a continuously evolving technology environment.
 * Business-fluent German and English.

## Description

Work side by side with assurance teams working on audit, internal controls, enterprise risk management and project excellence governance, understand real business challenges and rapidly engineer secure, scalable and reusable software, data and AI solutions that deliver measurable impact, You combine modern software engineering with hands-on experience in generative and agentic AI. Working closely with Product Owners and DevSecOps partners, you contribute across the solution lifecycle, from discovery, requirements and architecture to development, integration, deployment and continuous improvement. You build solutions with reuse in mind, creating scalable components that can be applied to similar challenges across different areas of assurance.
What You Will Do

 * Discover and prioritize: Work directly with assurance teams to understand complex business challenges, assess digitalization potential and independently identify and prioritize software, data and AI use cases with clear business value
 * Shape the digital landscape: Translate functional needs from Audit, Internal Controls, Enterprise Risk Management and Project Excellence into scalable solution concepts and actively shape the strategic digitalization and technology landscape for FIN A.
 * Engineer solutions end to end: Take technical ownership from solution design and architecture through development and integration to productive deployment, ensuring secure, scalable, maintainable and user-centered solutions.
 * Build with modern technologies: Lead and coordinate the development of modular applications, interfaces and data flows using technologies such as Python, Snowflake, Azure cloud and low-code platforms such as Mendix.
 * Shape and apply AI strategically: Co-create the AI strategy for FIN A and translate it into practice by designing and introducing GenAI applications, AI agents and agentic workflows with appropriate governance, guardrails and control mechanisms.
 * Move solutions into production: Drive validated prototypes and MVPs towards production-ready solutions together with Product Owners and DevSecOps partners, making sound technical decisions and actively managing dependencies, risks and trade-offs.
 * Design for scale and reuse: Define reusable solution patterns and components that can be transferred across assurance teams and integrated sustainably into the existing application landscape.
 * Drive adoption and measurable impact: Enable data- and AI-driven transformation across FIN A, measure delivered business value, continuously improve solutions and systematically transfer knowledge and capabilities to assurance teams.