Senior Director Information Technology

Expect more. Connect more. Be more at Diebold Nixdorf.  Our teams automate, digitize, and transform the way more than 75 million people around the globe bank and shop in this hyper-connected, consumer-centric world. Join us in connecting people to commerce in this vital, rewarding role.

The Senior Director, AI and Data Platform will be responsible for shaping and leading IT’s enterprise capability in artificial intelligence, data platforms, and analytics. This is a new leadership position created to accelerate the organization’s ability to deploy AI responsibly and at scale, while also transforming the underlying data and analytics environment needed to support future business growth.

The role will provide IT leadership for AI, partnering with key stakeholders to identify, assess, prioritize, and deliver AI use cases that create measurable business value. This includes establishing the technical, architectural, engineering, and operational capabilities required to move from experimentation to production-grade AI solutions. The role will lead the AI engineering effort, ensuring that AI solutions are robust, secure, scalable, maintainable, and aligned with technology standards.

The role will develop and operate the organization’s AI guardrails and governance model. The Senior Director will work across IT (including information security), legal, compliance, data privacy, risk, procurement, and business leadership to ensure AI is adopted safely, ethically, and in line with company policies. This will include defining decision rights, review processes, platform standards, reusable patterns, approved tools, data controls, and lifecycle management for AI solutions.

The role will also lead Data and Analytics for IT. This includes transforming the current data infrastructure, data operating model, analytics capabilities, and ways of working. The Senior Director will be accountable for developing a modern, scalable data platform strategy; improving data quality, accessibility, governance, and integration; and enabling stronger analytics, reporting, and self-service insight capabilities across the organization.

The successful candidate will be a strategic technology leader with strong execution discipline. They will combine enterprise IT leadership experience with deep understanding of AI, data platforms, analytics, cloud technologies, governance, and engineering delivery. They must be able to operate at executive level while also providing practical direction to teams responsible for platforms, products, data pipelines, AI engineering, governance, and analytics enablement.

• Lead the Diebold Nixdorf IT strategy and roadmap for AI, data platforms, and analytics, aligned to business priorities and the CIO’s technology agenda.

• Partner with senior business and functional stakeholders to identify, evaluate, prioritize, and sequence AI use cases based on value, feasibility, risk, readiness, and strategic alignment.

• Establish and lead the IT capabilities required to deliver AI at scale, including AI engineering, solution architecture, platform enablement, model lifecycle practices, integration patterns, testing, monitoring, support, and continuous improvement.

• Lead the AI engineering function, ensuring AI solutions are designed and delivered using robust software engineering, data engineering, security, architecture, and operational practices.

• Develop, implement, and continuously improve Diebold Nixdorf AI guardrails, including standards for responsible AI use, data protection, security, human oversight, transparency, vendor use, model management, and production deployment.

• Lead AI governance across IT, working closely with cybersecurity, legal, compliance, risk, privacy, procurement, enterprise architecture, and business stakeholders to establish clear decision rights, review processes, and control points.

• Define and manage the approved AI technology ecosystem, including enterprise AI platforms, development tools, reusable components, integration patterns, and vendor solutions.

• Build and mature the organization’s AI delivery model, balancing experimentation, proof of concept activity, production delivery, reuse, risk management, and measurable business outcomes.

• Lead Data and Analytics for IT, including the transformation of existing data infrastructure, reporting platforms, analytics capabilities, and data ways of working.

• Develop and execute a modern data platform strategy that supports analytics, AI, automation, reporting, operational insight, and future digital capabilities.

• Improve enterprise data quality, accessibility, integration, lineage, metadata, governance, and lifecycle management in partnership with business data owners and technology teams.

• Establish stronger analytics capabilities across IT and the wider business, including self-service analytics, executive dashboards, operational reporting, advanced analytics, and data product practices.

• Lead the transition from legacy or fragmented data environments toward more scalable, governed, cloud-enabled, and product-oriented data capabilities.

• Build, lead, coach, and develop a high-performing multidisciplinary team across AI engineering, data engineering, platform management, analytics, and governance.

• Manage team priorities, capacity, performance, budget, vendor relationships, delivery plans, and operating metrics.

• Work closely with Enterprise Architecture to ensure AI, data, and analytics solutions align with enterprise architecture principles, technology standards, integration strategy, and long-term platform direction.

• Partner with information security and infrastructure teams to ensure AI and data platforms are secure, resilient, compliant, observable, and operationally sustainable.

• Establish KPIs and value measures for AI, data, and analytics initiatives, including adoption, productivity, cost, quality, risk reduction, speed to delivery, and business impact.

• Communicate progress, risks, decisions, and recommendations clearly to the CIO, executive stakeholders, governance bodies, and cross-functional leadership teams.

• Stay current with developments in AI, data platforms, analytics, cloud, automation, and responsible AI, translating relevant trends into practical enterprise opportunities.

• Significant experience in senior IT, data, analytics, AI, digital, or technology leadership roles within a complex enterprise environment.

• Demonstrated ability to lead enterprise-scale AI, data platform, analytics, cloud, or digital transformation initiatives.

• Strong understanding of generative AI, machine learning, AI engineering, data engineering, analytics platforms, cloud data architectures, integration patterns, and enterprise technology delivery.

• Proven experience developing technology strategy, roadmaps, operating models, governance processes, and scalable delivery capabilities.

• Experience leading AI use case prioritization, AI delivery, responsible AI practices, or AI governance in an enterprise context.

• Strong understanding of data governance, data quality, metadata, data lineage, master data concepts, data integration, reporting, analytics, and self-service business intelligence.

• Experience modernizing data infrastructure, including cloud-based data platforms, data lakes, data warehouses, lakehouse architectures, or equivalent enterprise data environments.

• Strong people leadership experience, including building, managing, and developing multidisciplinary technical teams.

• Ability to influence and align senior stakeholders across business functions, IT, cybersecurity, legal, compliance, procurement, privacy, risk, and enterprise architecture.

• Strong commercial and vendor management capability, including experience assessing, selecting, implementing, and governing third-party technology solutions.

• Excellent judgment in balancing innovation, speed, risk, governance, security, cost, and operational reliability.

• Strong executive communication skills, with the ability to explain complex AI, data, and technology topics in clear business terms.

• Experience operating in a global or matrixed organization is preferred.

• Experience in manufacturing, services, supply chain, or similarly complex operational environments is advantageous.

• Bachelor’s degree in computer science, engineering, data science, information systems, business, or a related discipline preferred; advanced degree or relevant certifications are advantageous.

• Based in the United States and able to work effectively in a remote leadership role, with periodic travel as required.