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München, Bayern, Deutschland
Onsite
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
We are seeking an engineering leader to drive the next evolution of employee digital interaction across EMEA. As the leader of End User Support Engineering at EMEA IT, NVIDIA, you will sit at the intersection of IT infrastructure, Support, agentic AI, and engineering excellence — owning the full lifecycle of how employees across the region experience technology. This is not a traditional IT support leadership role. You will build and lead a team of engineers who support productivity of employees in the region and globally. In addition, you will design, automate, and continuously improve the employee productivity through scalable engineering practices, AI workflows, and a deep commitment to operational reliability.
What you will be doing:
In this engineering leader role, you will define and carry out an engineering roadmap for EMEA end user support. The roadmap will match the global IT strategy and business priorities.
Lead the strategy and execution for embedding agentic AI into IT support workflows — from intelligent triage and self-healing systems to fully autonomous resolution pipelines. Partner with AI/ML teams to design, deploy, and iterate on AI agents that reduce ticket volume, accelerate resolution, and proactively prevent issues before employees notice them.
Lead with a product outlook: treat the employee technology experience as a product, with critical metrics, iteration cycles, and continuous improvement loops. Identify friction points in the employee technology journey and engineer solutions that measurably improve experience, satisfaction, and productivity.
Build and develop a high-performing, geographically distributed engineering team across EMEA; mentor engineers and engineering managers at all levels.
Define and own EMEA-specific objectives and key results, SLAs, and engineering KPIs for end user support; report progress to senior leadership with clarity and accountability.
Build trusted relationships with regional business leaders, HR, Legal, and Workplace teams to align IT engineering investments to workforce needs. Represent EMEA as an engineering site leader, influencing global IT decisions with regional context and data-informed insights.
Act as the incident response leader for EMEA, ensuring continuous site operations and health, driving global incident response and resolution, and ensuring platform reliability through proactive monitoring, automation, and incident response frameworks aligned to enterprise SLAs.
Demonstrate excellent leadership and communication skills, with a proven history of building positive relationships with the business and enabling successful outcomes.
What we need to see:
10+ overall years of experience in IT engineering, infrastructure, or end user technology, with at least 4 years in people management or engineering leadership roles.
Demonstrated track record of leading engineering teams at scale in complex, multi-country or multi-regional environments — EMEA experience strongly preferred.
Hands-on background in systems/infrastructure engineering: strong prior individual contributor experience in at least one area (endpoint engineering, network, identity, cloud platforms, or automation).
Proven experience in crafting and deploying AI-powered workflows involving AI/ML operations concepts. Skilled in creating timely instructions and agentic workflow build within an IT or engineering context.
Experience with observability and monitoring platforms (Datadog, Splunk, Grafana, or similar) applied to IT operations.
Minimum of a BSc degree in Computer Science, Information Technology, Engineering, or a related technical field. Advanced degree (MSc/PhD) is preferred.
Ways to stand out from the crowd
Strong engineering approach with deep expertise in scalable platform architecture, automation, observability, reliability engineering, and modern operational practices including data-informed operations and AI-assisted service delivery.
Demonstrated expertise in SRE and platform reliability principles
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fuelled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to tackle, that only we can pursue, and that matter to the world. This is our life’s work, to amplify creativity and intelligence. Make the choice to join us today.