.What makes us Qlik? A Gartner Magic Quadrant Leader for 14 years in a row, Qlik transforms complex data landscapes into actionable insights, driving strategic business outcomes. Serving over 40,000 global customers, our portfolio leverages pervasive data quality and advanced AI/ML capabilities that lead to better decisions, faster. We excel in integration and governance solutions that work with diverse data sources, and our real-time analytics uncover hidden patterns, empowering teams to address complex challenges and seize new opportunities. The AI / ML Program Manager Role As an AI & Machine Learning Program Manager, you'll lead our AI initiatives from concept to deployment, driving innovation and shaping the future of AI at Qlik. You'll own the end-to-end execution of AI programs, from building reusable frameworks for machine learning models to establishing best practices in MLOps. In close collaboration with engineering leaders and stakeholders, you'll work to identify and tackle long-term infrastructure challenges, accelerating delivery and optimizing outcomes across projects. What makes this role interesting? This position offers an exciting opportunity to develop and implement AI strategies that can redefine data-driven insights for our clients. You'll be at the forefront of strategic AI projects, collaborating across teams to create impactful solutions and enable stakeholders to unlock the full potential of AI. You'll shape the frameworks and best practices that guide our machine learning model development, enabling rapid deployment and more efficient processes for our AI initiatives. Additionally, your expertise will help evaluate new AI-driven business opportunities and lead projects from planning through execution—ensuring meaningful impact across the organization. Here's how you'll be making an impact: Strategy Development: Partner with teams to create AI strategies and roadmaps, set goals, and uncover new opportunities for leveraging AI in business solutions. Project Leadership: Oversee AI initiatives from initial concept through execution, including budgeting, resource management, and maintaining high-quality outcomes. Enhanced Frameworks: Develop and enhance reusable frameworks for AI/ML models, drive MLOps best practices, and help engineering teams improve efficiency. Risk Management: Identify potential risks early and implement strategies to mitigate them, keeping projects on track. Innovation and Improvement: Stay current with emerging AI tech, recommending improvements to frameworks, processes, and tools to push the envelope in AI advancement at Qlik