AI Software Engineer, GS D
About the Role
Location Portugal Lisboa Amadora
1. Country: PORTUGAL
2. State/Province/County: Porto
3. City: Perafita
Remote vs. Office Hybrid (Remote/Office) Company Siemens Energy Unipessoal Lda. Organization Gas Services Business Unit Distributed Full / Part time Full-time Experience Level Mid-level Professional
A Snapshot of Your Day
Join our innovative team as an AI professional and lead the charge in energy transformation As a vital member of the Gas Services Distributed Digital Operations team, you'll redefine what's possible in industrial AI applications. Imagine crafting AI infrastructure and practices that set new industry benchmarks, all while enjoying the autonomy and resources to deliver groundbreaking solutions. If you're passionate about building AI systems that operate at the cutting edge of technology, we want to hear from you.
How You'll Make an Impact
4. Define and own end-to-end software architecture for cloud-native, data-intensive, and AI-enabled applications, ensuring scalability, reliability, and security on platforms like AWS.
5. Lead the design of microservices, APIs, and event-driven integrations to enable data products, analytics platforms, and AI workloads with high-quality, well-governed data.
6. Partner with data and AI engineers to embed Retrieval-Augmented Generation, recommender systems, and other AI capabilities into production services.
7. Drive cloud-native modernization initiatives, refactoring monoliths into modular architectures and guiding teams through PoCs and co-creation activities.
8. Establish and promote architecture standards, reusable patterns, and best practices for secure software development, API design, and CI/CD.
9. Act as a technical lead for distributed engineering teams, providing hands-on guidance in Java,, Python, and JavaScript frameworks.
What You Bring
10. Over 7 years of experience in software engineering and architecture, including recent experience as a Software Architect or IT Architect.
11. Strong background in designing and implementing distributed systems using Java,, Python, and modern JavaScript frameworks.
12. Hands-on experience with public cloud platforms (preferably AWS) and cloud-native runtimes such as containers and Kubernetes.
13. Solid understanding of data-intensive application design, including working with relational databases and search technologies.
14. Familiarity with AI and data use cases such as system integration with AI services and RAG-based solutions.
15. Proven experience leading or mentoring engineering teams and driving Agile ways of working.