Senior Generative AI Tech Lead

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

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 a