Senior Generative AI Tech Lead / Architect (m/f/d)

Create a better #TomorrowWithUs 🚀

At Siemens, we build technology solutions to shape the world we live in. We transform industries and societies by combining the real and digital worlds. With over 300.000 of the world’s most forward-thinking minds and the power of a presence in more than 190 countries, we make a truly global impact.

Are you ready to be part of the change? Come join us!  ⭐

Your mission will be… 

The Senior Generative AI Tech Lead is a key member of the Siemens Cybersecurity (CYS) organization, operating at the intersection of technical leadership, Generative AI engineering, and strategic planning. This role sits within the CYS AI & Platforms team and carries a dual mandate: driving hands-on technical delivery of Generative AI solutions across cybersecurity and productivity use cases, while co-shaping the long-term AI strategy for the CYS organization.

The Senior Generative AI Tech Lead leads projects end-to-end — from solution design and architecture to prototyping and implementation — and acts as a key contributor to the CYS AI governance model, reusable blueprint development, and cross-team AI initiative coordination. She/He translates complex business and cybersecurity requirements into scalable, secure, and production-grade Generative AI solutions built on top of the Siemens foundation AI platform, which leverages Microsoft Azure.

Responsibilities

• Lead projects end-to-end as Tech Lead: own solution design, architecture definition (4+1 Architectural View Model), prototyping, and implementation guidance across Generative AI use cases in cybersecurity and productivity increase domains.
• Design and architect scalable Generative AI solutions leveraging techniques such as Retrieval-Augmented Generation (RAG), Agentic AI, prompt engineering, fine-tuning, and multi-modal AI, built on top of the Siemens CYS AI platform.
• Support the CYS Platforms Department in defining and executing a long-term AI strategy, contributing to governance frameworks, portfolio visibility, and structured onboarding of AI use cases across CYS.
• Develop reusable blueprints, architecture patterns, and guidelines for secure Generative AI components and common CYS use cases, promoting standardization, reuse, and faster time-to-implementation.
• Support a shared vendor and technology strategy across CYS, contributing to the reduction of fragmentation and improving alignment on AI services and architectural choices (e.g., Azure OpenAI, LangChain, Hugging Face).
• Collaborate with the CYS AI Strategy team on prioritizing AI initiatives, identifying overlaps across teams, and coordinating efforts in a structured and transparent way.
• Enable a standardized operational support model by promoting best practices in AI monitoring, lifecycle management, ownership definition, and maintenance across CYS AI use cases.
• Mentor and guide team members on Generative AI engineering practices, code quality, and solution design, fostering a culture of technical excellence.
• Collaborate with cross-functional stakeholders — including cybersecurity analysts, platform engineers, and business owners — to gather requirements and translate them into AI-driven solutions.
• Design AI experiments, evaluate results, and communicate findings clearly to both technical and non-technical audiences.
• Apply advanced skills to resolve complex, cross-functional problems independently and with a high level of critical thinking.

We are looking for someone with…

• BS/BA in Computer Science, Computer Engineering, Mathematics, or a related discipline; advanced degree (MSc/PhD) preferred, or equivalent combination of education and experience.
• Typically 5+ years of successful work experience, with multiple years in AI/ML engineering, solution architecture, or a related technical leadership role.
• Strong proficiency in Python as the primary programming language for AI/ML development; proven skills in structuring code and applying software design patterns.
• Hands-on experience with Generative AI techniques and frameworks, including:
• Retrieval-Augmented Generation (RAG)
• Agentic AI / AI Agents (e.g., LangGraph, AutoGen, CrewAI, ArizeAI)
• LLM orchestration frameworks (e.g., LangChain, LlamaIndex)
• LLM APIs and model services (e.g., Azure OpenAI, OpenAI API, Hugging Face)
• Prompt engineering and fine-tuning strategies
• Proven experience with cloud platforms, with Microsoft Azure strongly preferred (e.g., Azure OpenAI Service, Azure AI Studio, Azure Machine Learning); AWS experience also valued (e.g., Amazon SageMaker, AWS Bedrock).
• Experience designing and deploying production-grade AI/ML applications, including CI/CD pipelines, monitoring, and lifecycle management.
• Demonstrated ability to lead technical initiatives and provide thought leadership across cross-functional teams.
• Experience contributing to or defining AI governance frameworks, architecture standards, or technology strategies at team or department level.
• Strong written and verbal communication skills in English, including professional maturity and presentation skills.
• Demonstrated ability to work independently, follow and drive execution plans, and adapt quickly to a fast-paced environment.
• Demonstrated ability to train and guide colleagues, promoting knowledge sharing and technical growth.
• Preferred Knowledge/Skills, Education, and Experience
• Microsoft Azure Certification is of advantage; e.g., Azure AI Engineer Associate, Azure Solutions Architect, Azure Data Scientist Associate.
• Familiarity in Cybersecurity domains — such as threat detection, security operations, vulnerability management, or identity & access management — is a strong plus.
• Familiarity with secure AI design principles, responsible AI practices, and AI risk management frameworks.
• Experience with data engineering and integration frameworks; e.g., event-driven architectures, message queues, databases, and data pipelines.
• Knowledge of containerization and orchestration technologies such as Docker or Kubernetes.
• Experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-Learn.
• Understanding of AI portfolio management and structured approaches to initiative prioritization (e.g., roadmapping, OKRs, value assessment).
• Experience working in or with Security Operations Centers (SOC) or cybersecurity platforms is of advantage.

Please attach your CV in English to your application.

#Siemens #Cybersecurity 

Siemens is deeply committed to fostering a diverse and inclusive environment. We are proud to be an equal opportunity employer and strongly encourage applications from a wide array of talented individuals!