AI Application Engineer - Enterprise systems

 

About the job

As part of our Enterprise Systems team, we are looking for an AI Application Engineer who will take ownership of the AI landscape within our internal systems ecosystem. 

While each application already includes AI features managed by the respective application owners, we need a centralized functional and technical expert to design, implement, and optimize AI solutions within our enterprise architecture, as well as oversee the development tools and AI-enhanced capabilities used throughout the software development lifecycle (SDLC). This includes configuring and integrating AI capabilities, developing and deploying AI models where needed, and ensuring these solutions are maintainable, secure, and aligned with organizational standards. 

Beyond the technical responsibilities, the AI Application Engineer will also act as an AI ambassador, guiding the organization in understanding the potential of AI, supporting responsible adoption, and ensuring business teams make effective use of AI functionality. They will work closely with functional and technical application engineers, process owners, and the data team to evaluate use cases, run pilots, and turn promising ideas into operational solutions. 

Key Responsibilities 

AI Strategy & Enablement 

• Serve as the central point of contact for AI applications within Enterprise Systems. 

• Advocate for responsible and effective AI adoption across the organization. 

• Translate business needs into AI-driven workflow opportunities and identify integrations with existing systems. 

• Build and prioritize our AI roadmap across different applications and business processes. 

• Identify and set up AI-related initiatives in our enterprise architecture and SDLC. 

• Support the evaluation, piloting, & adoption of AI-driven (development) tools in alignment with engineering best practices and security policies. 

AI Project Coordination 

• Coordinate AI-related initiatives, from initial opportunity assessment to implementation. 

• Work with application owners to ensure AI features are properly configured, governed, and maintained. 

• Align with the data team on data readiness, data flows, and opportunities involving analytics or machine learning. 

• Manage cross-functional AI pilots and ensure scalable handovers into production where relevant. 

• Collaborate with engineering teams to integrate AI into the SDLC, ensuring smooth use of AI for coding, testing, documentation, requirements analysis, and deployment workflows. 

Operational Support & Governance 

• Provide second-line support for AI features embedded in enterprise applications. 

• Ensure system-level AI features follow internal guidelines for compliance, privacy, and security. 

• Monitor and evaluate AI performance, quality, and usage metrics. 

• Maintain documentation and contribute to AI governance best practices. 

• Monitor and optimize tool performance, licensing, usage patterns, and integration into business & development workflows. 

Stakeholder Engagement 

• Collaborate with process owners, stakeholders and centers of excellence (e.g. service delivery, software engineering,...) to identify AI based workflow optimizations. 

• Train and inform business users about AI capabilities, limitations, and changes. 

• Promote a culture of safe and effective AI usage that optimizes workflows and reduces repetitive, time‑intensive work. 

 

 

Your Interests and Skills

Must-Have 

• Strong understanding of AI concepts and practical applications (e.g. generative AI, predictive models, automation). 

• Experience with cloud platforms (e.g. Azure, AWS) and modern AI tooling (e.g. Microsoft Copilot ecosystem, ChatGPT and Claude). 

• Experience working with enterprise systems, functional/technical application management, or data-driven solutions 

• Ability to translate business needs into technical AI requirements and vice versa. 

• Ability to separate short-lived hype from durable, meaningful innovation. 

• Experience with innovation funnel type of approaches (where a lot of pilots are started, continues evaluation and moving potential cases into production with a documented business case). 

• Project coordination experience, preferably in cross-functional environments. 

• Excellent communication skills and the ability to guide non-technical stakeholders. 

Nice-to-Have 

• Familiarity with data warehousing, business intelligence, or data engineering concepts. 

• Experience with AI governance frameworks or responsible AI principles. 

• Understanding integration patterns, APIs, or system architectures. 

• Hands-on experimentation or prototyping with AI tools. 

• Experience with Atlassian tooling, Workato, NetSuite, Salesforce, etc 

• Experience with development tools, CI/CD pipelines, or AI-enabled engineering platforms OR a strong willingness to develop expertise in this area. 

 

What we offer you