Senior Product Manager (German Speaking) — AI and Data Solutions

Germany / Austria / RomaniaFull-TimeSenior
Salary not disclosed
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Job Details

Languages
Advanced English and German language skills.
Experience
5–7+ years in product management (0→1 and scaling) 3–5+ years with AI/ML, GenAI, or data platforms
Required Skills
AWSAgileArtificial IntelligenceFigmaGCPGitMicrosoft Power BIProduct ManagementSCRUMJiraTableauAzureRESTful APIsData modelingConfluencePrompt EngineeringLLMMLOpsGenerative AILangChain

Requirements

  • 5–7+ years in product management (0→1 and scaling)
  • 3–5+ years with AI/ML, GenAI, or data platforms
  • Strong Agile/Scrum experience
  • Experience in a client-facing / consulting environment
  • Advanced English and German language skills
  • Technical expertise in GenAI: prompt engineering, RAG, embeddings, vector DBs
  • Technical expertise in Agentic AI: LangChain, AutoGPT, CrewAI
  • Technical expertise in Data: ETL/ELT, data modeling, migration strategies
  • Technical expertise in Cloud: AWS, Azure, GCP + platforms (Snowflake, Databricks, BigQuery)
  • Familiarity with MLOps, model deployment, AI observability
  • Tools: Jira, Confluence, Figma, Tableau/Power BI, Git
  • Design thinking, data-driven decision making, strong communication, and storytelling
  • Bias toward action; thrives in ambiguity with structured problem-solving
  • Engineering thinking, understanding of AI-native development toolset
  • Fluent in AI-powered automation, with hands-on experience building productivity tools

Responsibilities

  • Define product vision and roadmaps for GenAI/LLM solutions (GPT-4, Claude, Llama, Gemini), RAG, and Agentic AI
  • Own end-to-end product lifecycle (0→1 and scale) aligned with business KPIs
  • Build business cases (market analysis, ROI, competitive positioning)
  • Lead large-scale data migration across AWS, Azure, GCP
  • Oversee data pipelines, transformation, governance, and APIs
  • Lead Agile processes, backlog grooming, and sprint planning
  • Work with clients, engineers, data scientists, and UX teams
  • Translate technical solutions into business value
  • Define success metrics and analytics frameworks
  • Support product adoption and change management
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