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Spotify

Staff Backend Engineer - Content Platform

Spotify is hiring a Staff Backend Engineer - Content Platform in London, United Kingdom. Level rates it ; you can apply on Spotify.

Level's read on this job

  • Level rates this software engineer role Little AI ●○○○: aI is not part of the work.
  • Level classes it as a lead role.
  • Spotify has 84 other open roles on Level.
  • Posted within the past week.

AI in this role

We design Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.

Policy & Safety (P&S) is a domain within Content Platform in the Experience Mission, responsible for building Spotify’s content moderation and regulatory compliance infrastructure. This includes rule engines, enforcement pipelines, policy configuration systems, and compliance data platforms that ensure safety at scale.

The team operates at the intersection of backend platform engineering, machine learning systems, and regulatory compliance, partnering closely with Licensing, Trust & Safety, Legal, and Public Affairs. Sitting on the critical path for every new content type and feature, P&S enables safety-by-default experiences while supporting global regulatory requirements and evolving product innovation.

What you'll Do

  • Define the technical direction for policy enforcement infrastructure

  • Architect enforcement capabilities as a shared platform designed to be consumed by multiple product teams rather

  • Design and evolve multi-signal orchestration systems that enable configurable, auditable policy enforcement at scale across content types and product surfaces

  • Build the data foundation that makes enforcement decisions durable and reusable

  • Own the hardest API and contract decisions: schema design, versioning strategy, and how enforcement interfaces evolve without breaking the teams that depend on them

  • Establish integration standards for teams onboarding onto shared enforcement infrastructure, and work directly with consuming teams to execute migrations with clean cutoffs and clear end states

  • Influence architecture across detection, signal processing, and enforcement workflows so that the underlying primitives stay coherent as the platform scales

  • Mentor engineers and set the bar for how the team reasons about API design, data modeling, and the downstream compliance consequences of infrastructure choices

Who You Are

  • Deep experience designing and operating large-scale distributed systems, APIs, event-driven pipelines, rule engines, and decision systems running in production across high-throughput environments

  • Proficient in backend engineering at scale, with strong command of languages like Java, Kotlin, Go, or similar; comfortable owning data models, service contracts, and storage layer decisions

  • Experienced with stream processing and event-driven architectures (Kafka, Pub/Sub, or equivalent) and the tradeoffs between batch and real-time enforcement pipelines

  • You have designed systems where schema and contract stability matter as much as correctness

  • Experienced with workflow orchestration and distributed coordination, whether through dedicated orchestration frameworks like Temporal or Airflow, choreography-based event systems, or hybrid approaches, and understand the tradeoffs between each in the context of long-running, stateful enforcement workflows

  • Experienced with relational and non-relational storage systems and know how to model enforcement data for auditability, immutability, and efficient querying at scale

  • You understand platform engineering patterns: multi-tenant APIs, configurable rule engines, policy-driven actioning systems, and the difference between building for one team and building for many

  • Familiar with observability and operational excellence, distributed tracing, structured logging, alerting, and the tooling that makes enforcement systems debuggable and auditable in production

  • You have worked in regulated or compliance-adjacent environments and understand how infrastructure design decisions, log retention, schema choices, data lineage, carry legal and audit consequences

  • You are comfortable in polyglot environments and can navigate existing systems thoughtfully rather than defaulting to greenfield rewrites

  • You think in systems end-to-end

Where You'll Be

  • This role is based in London or Stockholm.

  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens. At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.

How we rate this

Staff Backend Engineer - Content Platform at Spotify rates 30 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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