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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
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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.
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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.
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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.
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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.
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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).
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Collaborate with the CYS AI Strategy team on prioritizing AI initiatives, identifying overlaps across teams, and coordinating efforts in a structured and transparent way.
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Enable a standardized operational support model by promoting best practices in AI monitoring, lifecycle management, ownership definition, and maintenance across CYS AI use cases.
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Mentor and guide team members on Generative AI engineering practices, code quality, and solution design, fostering a culture of technical excellence.
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Collaborate with cross-functional stakeholders — including cybersecurity analysts, platform engineers, and business owners — to gather requirements and translate them into AI-driven solutions.
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Design AI experiments, evaluate results, and communicate findings clearly to both technical and non-technical audiences.
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Apply advanced skills to resolve complex, cross-functional problems independently and with a high level of critical thinking.
We are looking for someone with…
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BS/BA in Computer Science, Computer Engineering, Mathematics, or a related discipline; advanced degree (MSc/PhD) preferred, or equivalent combination of education and experience.
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Typically 5+ years of successful work experience, with multiple years in AI/ML engineering, solution architecture, or a related technical leadership role.
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Strong proficiency in Python as the primary programming language for AI/ML development; proven skills in structuring code and applying software design patterns.
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Hands-on experience with Generative AI techniques and frameworks, including:
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Retrieval-Augmented Generation (RAG)
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Agentic AI / AI Agents (e.g., LangGraph, AutoGen, CrewAI, ArizeAI)
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LLM orchestration frameworks (e.g., LangChain, LlamaIndex)
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LLM APIs and model services (e.g., Azure OpenAI, OpenAI API, Hugging Face)
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Prompt engineering and fine-tuning strategies
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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).
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Experience designing and deploying production-grade AI/ML applications, including CI/CD pipelines, monitoring, and lifecycle management.
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Demonstrated ability to lead technical initiatives and provide thought leadership across cross-functional teams.
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Experience contributing to or defining AI governance frameworks, architecture standards, or technology strategies at team or department level.
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Strong written and verbal communication skills in English, including professional maturity and presentation skills.
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Demonstrated ability to work independently, follow and drive execution plans, and adapt quickly to a fast-paced environment.
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Demonstrated ability to train and guide colleagues, promoting knowledge sharing and technical growth.
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Preferred Knowledge/Skills, Education, and Experience
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Microsoft Azure Certification is of advantage; e.g., Azure AI Engineer Associate, Azure Solutions Architect, Azure Data Scientist Associate.
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Familiarity in Cybersecurity domains — such as threat detection, security operations, vulnerability management, or identity & access management — is a strong plus.
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Familiarity with secure AI design principles, responsible AI practices, and AI risk management frameworks.
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Experience with data engineering and integration frameworks; e.g., event-driven architectures, message queues, databases, and data pipelines.
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Knowledge of containerization and orchestration technologies such as Docker or Kubernetes.
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Experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-Learn.
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Understanding of AI portfolio management and structured approaches to initiative prioritization (e.g., roadmapping, OKRs, value assessment).
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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
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