AI Engineer / Data Scientist

• Use Case & Solution Design: Identify, scope, and translate business requirements and customer needs into concrete, actionable AI solutions and product concepts.
• Data Science & Machine Learning: Analyze behavioral transaction data and build/improve ML models for personalization - e.g. segmentation, churn prediction, and smart recommendations.
• Intelligent, Automated Features: Help develop AI-driven, personalized features across our platform, from automated messaging to smart campaign optimization.
• LLM Integration & Grounding: Integrate large language models into our product, establishing RAG architectures and robust evaluation to ensure reliable, high-quality output at scale.
• Data & ML Pipelines: Work with large-scale behavioral data, ensure data quality, and collaborate with backend teams to bring data pipelines and models reliably into production.
• Prototyping & Impact: Rapidly prototype with modern AI tools, validate ideas directly on real data, and run evaluations to prove the real-world business impact of AI features.

• Solution Engineering & Technical Consulting: Background in tech consulting, solution engineering, or applied AI where you translated business needs into technical solutions.
• Applied AI & Python Skills: Confident in Python (e.g., Pandas, basic ML frameworks) and hands-on experience using modern AI tools/APIs (OpenAI, Anthropic, LangChain, etc.) to quickly build working scripts and prototypes.
• Data Science & ML Foundations: Practical grasp of classical machine learning, data analysis, and predictive modeling on tabular/behavioral data - applied pragmatically, not purely academically.
• LLM & GenAI Foundations: Practical experience with modern language models - including prompting, RAG/grounding, tool use, and systematic benchmarking of AI outputs.
• Business & Impact Mindset: You naturally start with the “why” and the business value before writing code, prioritizing practical feasibility over pure research.
• Strong Communication & Alignment: Ability to communicate complex technical concepts clearly to both technical developers and business stakeholders.
• Proactive Working Style: A structured, solution-oriented, and self-directed approach to solving open-ended problems.
• Language: Professional English skills; German is a welcome plus.
• Location: You are ready to join our team on-site in Leonding or Vienna.

• Frontier Topics from Day One: Shape our most strategic product initiatives - from Autopilot to our Intelligence Layer to autonomous, hyper-personalized communication.
• High Impact & Visibility: Play a central role in transforming strategic AI ideas into real, value-generating platform features used by millions.
• Growth & Mentorship: Advance your career in a culture of continuous learning, intensive onboarding, and proactive support.
• State-of-the-Art Tech: Work with a modern stack, modern AI tooling, and choose the hardware that maximizes your productivity.
• Flexibility & Hybrid Work: Enjoy a healthy work-life balance with flexible working hours and hybrid office options.
• Team Spirit: Join a cohesive, international team with numerous team events throughout the year, supported fitness memberships, and shared sports activities.

Let’s shape the future of digital loyalty together! We offer a base salary of € 60,000 gross per year, with a market-competitive overpayment depending on your track record and expertise.

At hello again, we empower companies to build lasting customer relationships through a sophisticated digital loyalty solution. We run 1,000+ white-label loyalty programs across Europe, serving 17M+ end consumers in 28 countries. As we move into the next era of loyalty, we are looking for an AI Solutions Engineer (d/f/m) to bridge the gap between strategic business goals and cutting-edge AI technology, shaping the intelligent core of our platform.

In this role, you turn transaction and behavioral data into scalable business value. You identify strategic AI use cases, rapid-prototype modern models and pipelines, and work closely with product and development teams to move us from a “tool to run loyalty” to a platform that “runs loyalty - and proves it works.”