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Engineering Manager - AI Innovation​/Lounge Zalando

in 10115, Berlin, Berlin, Deutschland
Unternehmen: Zalando SE
Vollzeit position
Verfasst am 2026-07-04
Berufliche Spezialisierung:
  • Software Entwicklung
    Backend Entwicklung, Künstliche Intelligenz Ingenieur, DevOps Ingenieur, Cloud-Ingenieur - Software
Gehalts-/Lohnspanne oder Branchenbenchmark: 80000 - 120000 EUR pro Jahr EUR 80000.00 120000.00 YEAR
Stellenbeschreibung
Stellenbezeichnung: Engineering Manager - AI Innovation / Lounge by Zalando (all genders)

Role & Team

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.

Inclusive by Design

At Zalando, our vision is to be inclusive by design. This vision starts with our hiring – we do not discriminate on the basis of gender identity, sexual orientation, personal expression, ethnicity, religious belief, or disability status. You are welcome to leave out your picture, age, or marital status from your application. We only assess candidates on their qualifications and merit.

We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need, so we can best support you throughout the hiring process.

Our diversity & inclusion strategy:
Our employee resource groups:

What We’d Love You to Do (and Love Doing)
  • Define the blueprint:
    Shape strategy and execution principles for turning AI opportunities into scalable capabilities (from prototypes to platform and product features).
  • Deliver measurable impact:
    Drive end‑to‑end delivery of AI‑enabled experiences with clear outcomes (conversion, CSAT, productivity, cost) and trustworthy measurement.
  • Engineer the product logic:
    Build the decisioning and orchestration that determines what the user sees and why (assistant flows, automation steps, ranking/selection, fallbacks).
  • 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 (queues/streams, caching, rate limiting, resilience patterns).
  • 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 (offline tests + online A/B experimentation).
  • Grow people and culture:
    Hire, coach, and develop engineers; foster a culture of ownership, feedback, and engineering excellence.
We’d Love to Meet You If You Have...
  • Proven Engineering Leadership:
    Significant experience as an Engineering Manager or a Technical Lead with direct people‑management responsibilities and a track record of building, developing, and retaining high‑performing, healthy engineering teams.
  • Strong backend foundation:
    You have built and operated distributed systems at scale (microservices, cloud‑native architectures, CI/CD, reliability patterns, message queues/streams).
  • Comfortable with JVM and modern stacks:
    You are familiar with JVM‑based backends (Java/Kotlin/Scala) and/or Python, and you can reason about APIs, data stores, and infrastructure.
  • AI product engineering mindset:
    You can translate AI possibilities into shippable software and you understand the difference between demos and production systems.
  • Familiar (not expert) in ML/LLM fundamentals:
    You do not need advanced ML expertise, but you understand concepts like embeddings, vector search, RAG, evaluation/metrics, prompt and workflow design, latency/cost trade‑offs, and experimentation.
  • You value observability:
    You use metrics, logs, tracing, define SLOs, and build systems that are diagnosable and supportable.
  • You are a systems thinker and collaborator:
    You can hold context across teams and codebases, align stakeholders, and make pragmatic trade‑offs.
Our Offer

Zalando provides a range of benefits. Here’s an overview of what you can expect.

  • Employee shares programme
  • 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

Ask your Talent Acquisition Partner to learn more about what we offer.

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