AI Product Strategy & Delivery

  • 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).

Data & Platform Initiatives

  • Lead large-scale data migration across AWS, Azure, GCP
  • Oversee data pipelines, transformation, governance, and APIs
  • Ensure data quality, security, compliance, and observability.

Agile Execution

  • Lead Agile processes, backlog grooming, and sprint planning
  • Break down complex features into incremental releases
  • Balance feature delivery with technical debt and architecture improvements.

Stakeholder Collaboration

  • Work with clients, engineers, data scientists, and UX teams
  • Translate technical solutions into business value
  • Run workshops, user research, and product validation.

Performance & Scaling

  • Define success metrics and analytics frameworks
  • Drive continuous improvement and root-cause analysis
  • Support product adoption and change management.

  • Lead top-tier engineering teams and cutting-edge agentic AI systems, enterprise AI platforms.

  • Shape how enterprises adopt AI — from strategy to architecture to delivery.

  • Grow within a team building modern AI-delivery practices, tools, and frameworks.

  • Remote-friendly culture with strong engineering, data, and consulting partnerships.

  • Experience

    • 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

    • GenAI: prompt engineering, RAG, embeddings, vector DBs
    • Agentic AI: LangChain, AutoGPT, CrewAI
    • Data: ETL/ELT, data modeling, migration strategies
    • Cloud: AWS, Azure, GCP + platforms (Snowflake, Databricks, BigQuery)
    • MLOps, model deployment, AI observability
    • Tools: Jira, Confluence, Figma, Tableau/Power BI, Git.

    Core Skills:

    • 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 for yourself or your team using Claude workflows/routines or similar tools, as well as automation platforms like n8n or equivalent.
    • Creativity, with experience building prototypes using Claude Code or similar tools.
    Provectus

    Provectus