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We are opening a new Engineering Manager role in AI Innovation to reflect our growing scope and transition from experimentation to scalable, production-grade AI capabilities. This is a high-impact leadership role where you will bridge modern AI (LLM-powered experiences, automation, and decision support) with reliable backend engineering and measurable business value. You will lead a team building AI-enabled products and platform capabilities used across consumer and internal journeys. We operate high-throughput services in a B2C environment and focus on shipping AI features that are safe, observable, and cost-efficient.
Verantwortlichkeiten
Define the blueprint: Shape strategy and execution principles for turning AI opportunities into scalable capabilities
Deliver measurable impact: Drive end-to-end delivery of AI-enabled experiences with clear outcomes
Engineer the product logic: Build the decisioning and orchestration that determines what the user sees and why
Integrate assistant frameworks: Bring assistants into real systems by integrating orchestration, tool/function calling, retrieval (RAG), and knowledge sources with strong security boundaries
Build for scale and reliability: Own high-load, real-time APIs and event-driven services
Operational excellence: Take accountability for SLOs, 24/7 readiness, incident response, and on-call maturity for critical services
Responsible AI by design: Implement guardrails for privacy, safety, and compliance
establish evaluation and quality gates
Grow people and culture: Hire, coach, and develop engineers
foster a culture of ownership, feedback, and engineering excellence
Anforderungen
Proven Engineering Leadership: Significant experience as an Engineering Manager or a Technical Lead with direct people management responsibilities
Strong backend foundation: built and operated distributed systems at scale
Comfortable with JVM and modern stacks: JVM-based backends (Java/Kotlin/Scala) and/or Python
AI product engineering mindset: translate AI possibilities into shippable software
Familiar (not expert) in ML/LLM fundamentals: embeddings, vector search, RAG, evaluation/metrics, prompt and workflow design, latency/cost tradeoffs, experimentation
Value observability: use metrics/logs/tracing, define SLOs, build diagnosable and supportable systems
Systems thinker and collaborator: hold context across teams and codebases, align stakeholders, make pragmatic tradeoffs
Was wir biete
Employee shares program
40% off fashion and beauty products sold and shipped by Zalando, 30% off Zalando Lounge, discounts from external partners
2 paid volunteering days a year
Hybrid working model with up to 60% remote per week
Work from abroad for up to 30 working days a year
27 days of vacation a year to start
Relocation assistance available (subject to prior agreement)
Family services, including counseling and support
Health and wellbeing options (including Gympass)
Mental health support and coaching available
Drive your development through our training platform and biannual peer-to-peer review
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