AI Principal Engineer

• 7–10+ years of experience in software engineering, machine learning, or applied AI 

• Strong experience designing and deploying production-grade systems in cloud environments 

• Experience building and deploying AI/ML systems, ideally with LLMs or generative AI 

• Experience in building, orchestrating, monitoring agentic/multi-agentic AI workflows 

• Ability to work across the stack (APIs, data pipelines, front-end interfaces when needed) 

• Deep understanding of system design, distributed systems, and scalable architectures 

• Solid system design skills with a focus on scalability, reliability, and security 

• Knowledge of data engineering and analytics workflows 

• Experience working in global, cross-functional teams 

• Familiarity with governance, security, and compliance considerations for enterprise AI 

• Proven ability to navigate ambiguity and move quickly in fast-paced environments 

• Strong product and user mindset focused on delivering practical, impactful solutions 

• Excellent communication skills; able to work directly with stakeholders across all levels 

• High ownership and bias for action, ability to support multiple workstreams in parallel 

• String experience in mentoring and guiding team members to make good decisions 

• Familiarity with enterprise systems (ERP, CRM, workflow tools) 

• Experience across Azure AI, Microsoft Copilot, and the broader Microsoft ecosystem 

• Experience implementing AI tools, GenAI services, building and orchestrating agentic AI workflows in real-world business processes 

• Experience in forward-deployed, solutions engineering, or consulting-style roles 

• Background in process optimization, automation, or digital transformation initiatives c

• High impact: Your work will directly improve how the company operates 

• Speed & autonomy: We are an agile team that ships quickly and iterates continuously 

• Broad exposure: Work across all business functions and geographies 

• Cutting-edge tech: Build with the latest AI technologies and shape how they are applied internally 

• Ownership: Drive projects end-to-end and see immediate adoption of your work 

Salary: 55300– €78.800 gross per year.  This role might also be eligible for a performance-based bonus. Placement within the range will depend on objective criteria including experience, skills, and internal equity considerations. We are committed to equal pay and pay transparency. Remuneration decisions are made using gender-neutral and objective criteria.​​

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)

We are looking for a Principal AI Engineer to join our Enterprise Productivity team, an agile, high-impact group building AI-driven solutions that transform how our company operates. 

In this role, you will work at the intersection of AI, engineering, and business operations, partnering directly with teams across the company to identify inefficiencies, rapidly prototype solutions, and deploy scalable AI tools that drive measurable impact. You will operate globally, engage with diverse stakeholders, and tackle high-leverage problems that improve how we work every day. 

This is a fast-moving, hands-on role for someone who thrives in ambiguity, enjoys solving real-world problems, and wants to see their work adopted quickly at scale.

• Identifying and delivering high-impact AI use cases that reduce manual work and 

• increase efficiency 

• Shipping production-ready solutions in weeks, with strong adoption across teams 

• Building scalable, reusable AI capabilities across the enterprise 

• Acting as a trusted technical partner to both engineering and business stakeholders 

• Embed with business teams to deeply understand workflows, pain points, and opportunities for automation and optimization 

• Design and build AI-powered tools that improve internal productivity across functions such as finance, HR, operations, sales, and marketing 

• Rapidly prototype and iterate using modern AI/ML technologies (e.g., LLMs, Copilots, automation pipelines) 

• Deploy solutions in production, ensuring reliability, usability, and measurable impact 

• Bridge technical and non-technical teams, translating business problems into scalable engineering solutions 

• Drive end-to-end delivery from problem discovery to implementation, rollout, and adoption 

• Create reusable frameworks and platforms to accelerate future AI deployments across the organization 

• Operate globally, collaborating with distributed teams and delivering solutions that scale across regions