AI Agentic Software Engineer

At Siemens, we help organizations transform maintenance and operations through connected insights, AI-powered technology, and intelligent asset management solutions. Our software enables customers to handle the full lifecycle of assets, facilities, and infrastructure while improving efficiency, reducing risk, and optimizing long-term investments. By connecting data, people, and processes, we empower organizations to make smarter decisions, improve asset performance, and achieve more resilient operations. 

Description: 

Siemens continues to grow and needs exceptional engineers. This is an excellent opportunity for versatile software professionals who thrive in a fast-paced, collaborative environment. You will work alongside our world-class engineering and product teams to design, implement, deliver, and support highly ambitious SaaS products and integrations. We are building a team that treats AI not as a novelty but as a core part of the engineering workflow — from AI-assisted coding and automated code review to agentic pipelines that amplify what individual engineers can deliver. You will bring your curiosity about these emerging practices and your passion for the craft of software engineering. 

YOU’LL MAKE AN IMPACT BY: 

- Build innovative, performant features into our next-generation SaaS applications, applying core computer science principles — data structures, algorithms, and design patterns — to deliver reliable, scalable solutions. 

- Design, implement, test, and document services and components that scale across multiple projects as common services or shared modules, within scope, cost, time, and quality constraints. 

- Embed quality throughout the full agile product lifecycle: requirements, design, code, testing, delivery, and production support — including owning root-cause resolution of production defects. 

- Write clean, maintainable code; uphold and continuously improve engineering standards in a professional environment (source control, CI/CD, shortened release cycles, automated testing). 

- Partner with product owners and senior engineers to translate user requirements into technical specifications, offering pragmatic feasibility guidance and data-driven decision making. 

- Leverage AI-assisted developer tools (e.g., GitHub Copilot, Claude, Cursor, or equivalent) to accelerate coding, code review, test generation, and debugging — and actively share practices and learnings with the team. 

- Participate in agentic development workflows where AI agents assist with or autonomously handle defined stages of the SDLC — such as story enrichment, scaffolding, test generation, and PR summarization — reviewing agent output critically and ensuring quality before merge. 

THIS IS HOW YOU’LL WIN US OVER: 

- Bachelor's degree in Computer Science or a related team, or equivalent professional experience. 

- 1–3 years of professional software engineering experience building and maintaining web-based or service-oriented applications. 

- Solid grounding in data structures, algorithms, object-oriented programming, SQL/databases, REST API design, and SOLID principles. 

- Experience with unit testing, mocking frameworks, and test automation — with a quality-first mindset across the full development lifecycle. 

- DevOps mindset: familiarity with CI/CD pipelines, exception handling, logging, monitoring, and operational metrics in a mature SDLC environment. 

- Strong communication, partnership, and teamwork skills; experience working in agile methodologies (Scrum, Kanban, or equivalent). 

YOU’LL THRIVE EVEN MORE IF YOU ALSO BRING 

- Hands-on experience with AI coding assistants and prompt engineering — using tools like GitHub Copilot, Claude, Cursor, or similar to accelerate code generation, test scaffolding, documentation, and code review. 

- Exposure to agentic development patterns: understanding how LLM-powered agents can be chained or orchestrated to automate multi-step engineering tasks (e.g., requirement analysis → code generation → test writing → PR creation), and experience evaluating or integrating such pipelines into a team workflow. 

- Familiarity with LLM tool-use, function calling, or structured output techniques that enable AI agents to interact with APIs, codebases, and external systems in a controlled, verifiable way. 

- Cloud platform exposure — AWS, Azure, or GCP — including containers (Docker) and orchestration (Kubernetes). 

- Experience with event-driven or messaging architectures (Kafka, SQS, RabbitMQ, or similar). 

- Open-source contributions, personal projects, hackathon participation, or active involvement in developer communities — especially AI/ML or developer-tooling focused. 

- Certifications in cloud platforms, AI/ML fundamentals, technology, or agile methodologies. 

- Prior experience in agile at scale across globally distributed teams. 

At Siemens, you'll have the opportunity to grow your career while helping organizations operate smarter, safer, and more sustainably. We foster a culture of innovation, collaboration, and continuous learning, where employees are empowered to make a difference every day. If you're excited about solving real-world challenges, building AI-augmented software, and shaping the future of asset management, we encourage you to apply.