Director, IT Engineering - End User Support

Posted Yesterday
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2 Locations
In-Office
Expert/Leader
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Lead EMEA End User Support Engineering to design and deliver scalable employee technology experiences. Define engineering roadmaps, embed agentic AI into support workflows, drive automation, observability, and SRE practices, own incident response, build distributed teams, set regional SLAs/KPIs, and partner with business leaders to improve productivity and reliability.
Summary Generated by Built In

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:

  • 12+ overall years of experience in IT engineering, infrastructure, or end user technology, with at least 6 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.

Skills Required

  • 12+ years of experience in IT engineering, infrastructure, or end user technology
  • At least 6 years in people management or engineering leadership roles
  • Proven track record of leading engineering teams at scale in multi-country or multi-regional environments
  • Hands-on background in systems/infrastructure engineering (endpoint engineering, network, identity, cloud platforms, or automation)
  • Proven experience crafting and deploying AI-powered workflows involving AI/ML operations concepts
  • 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
  • EMEA experience
  • Advanced degree (MSc/PhD)
  • Demonstrated expertise in SRE and platform reliability principles

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked 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 — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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