Engineering Manager - AI Innovation // Lounge by Zalando (all genders)

Role 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, operating high-throughput services in a B2C environment. Responsibilities - 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 and trustworthy measurement. - Engineer the product logic: Build the decisioning and orchestration that determines user-facing flows, automation, and ranking. - Integrate assistant frameworks: Bring assistants into real systems by integrating orchestration, tool/function calling, 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. - 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. Qualifications - Proven Engineering Leadership: Significant experience as an Engineering Manager or Technical Lead with direct people management responsibilities and a track record of building high-performing teams. - Strong backend foundation: Experience building and operating distributed systems at scale (microservices, cloud-native architectures, CI/CD, reliability patterns). - Comfortable with JVM and modern stacks: Familiarity with JVM-based backends (Java/Kotlin/Scala) and/or Python. - AI product engineering mindset: Ability to translate AI possibilities into shippable software. - Familiarity with ML/LLM fundamentals: Understanding of embeddings, vector search, RAG, evaluation/metrics, prompt design, and latency/cost tradeoffs. - Observability: Experience using metrics/logs/tracing and defining SLOs. - Systems thinking: Ability to hold context across teams, align stakeholders, and make pragmatic tradeoffs. What We Offer - Employee shares program and product discounts. - Hybrid working model with up to 60% remote per week and work-from-abroad options. - 27 days of vacation to start. - Relocation assistance, family services, and health/wellbeing support. - Professional development through training platforms and peer-to-peer reviews.