8 months ago
Berlin, GermanyStaff+
Responsibilities
- Lead and mentor a team of Applied Scientists and AI/ML Engineers.
- Define technical strategy for AI/ML solutions using structured CRM data and unstructured content.
- Build agentic workflows and real-time reasoning engines for the AI-native CRM.
- Partner with the AI Platform team on LLMOps strategy and robust model deployment.
- Design and optimize AI systems and data-intensive solutions for production performance and customer value.
- Serve as a technical authority, shape the AI engineering roadmap, and lead critical systems as a hands-on individual contributor.
Requirements
- 8+ years of applied science or engineering experience across the full ML and AI lifecycle in high-scale production environments.
- Proven ability to lead and scale technical teams, mentor senior talent, and raise organizational technical standards.
- Hands-on expertise with agentic system orchestration, including LangGraph, RAG architectures, and vector databases.
- Broad practical knowledge of ML, deep learning, AI, model trade-offs, and agentic frameworks.
- Demonstrated success delivering customer and business value through AI/ML solutions at scale.
- Strong product sense and ability to connect technical decisions to user outcomes.
- Ability to lead through influence and technical authority while partnering with platform teams.
- Understanding of AWS or GCP, distributed systems, container orchestration, and data engineering including batch pipelines, feature stores, and Kafka.
Benefits
- Flexible hours, wellness perks, and company SWAG.
- Performance-based bonuses, 28 paid leave days, well-being days, compassionate leave, and pawternal leave.
- Mentorship, coaching, internal mobility, and professional development support.
- Hybrid work arrangement.
- Meaningful work supporting more than 100,000 small and medium-sized businesses.
Tech Stack
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