{"id":3807770,"url":"https://alion.io/job/spotify-staff-backend-engineer-content-platform","title":"Staff Backend Engineer - Content Platform","company":{"id":57,"name":"Spotify","domain":"spotify.com","url":"https://alion.io/company/spotify","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":83,"open_postings":13,"ghost_share":0,"stale_share":0.615,"repost_share":0.077,"time_to_fill_p50_days":50,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Backend","role_family":"Backend","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom","Stockholm, Sweden"],"countries":["GB","SE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Kotlin","optional":false},{"name":"Machine Learning","optional":false},{"name":"Platform Engineering","optional":false}],"status":"live","first_seen_at":"2026-11-05T13:45:45Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-07T14:34:27Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"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.\nPolicy & 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.\nThe 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.\nWhat you'll Do\nDefine the technical direction for policy enforcement infrastructure\n\nArchitect enforcement capabilities as a shared platform designed to be consumed by multiple product teams rather\n\nDesign and evolve multi-signal orchestration systems that enable configurable, auditable policy enforcement at scale across content types and product surfaces\n\nBuild the data foundation that makes enforcement decisions durable and reusable\n\nOwn the hardest API and contract decisions: schema design, versioning strategy, and how enforcement interfaces evolve without breaking the teams that depend on them\n\nEstablish 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\n\nInfluence architecture across detection, signal processing, and enforcement workflows so that the underlying primitives stay coherent as the platform scales\n\nMentor engineers and set the bar for how the team reasons about API design, data modeling, and the downstream compliance consequences of infrastructure choices\n\nWho You Are\nDeep experience designing and operating large-scale distributed systems, APIs, event-driven pipelines, rule engines, and decision systems running in production across high-throughput environments\n\nProficient 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\n\nExperienced with stream processing and event-driven architectures (Kafka, Pub/Sub, or equivalent) and the tradeoffs between batch and real-time enforcement pipelines\n\nYou have designed systems where schema and contract stability matter as much as correctness\n\nExperienced 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\n\nExperienced with relational and non-relational storage systems and know how to model enforcement data for auditability, immutability, and efficient querying at scale\n\nYou 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\n\nFamiliar with observability and operational excellence, distributed tracing, structured logging, alerting, and the tooling that makes enforcement systems debuggable and auditable in production\n\nYou 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\n\nYou are comfortable in polyglot environments and can navigate existing systems thoughtfully rather than defaulting to greenfield rewrites\n\nYou think in systems end-to-end\n\nWhere You'll Be\nThis role is based in London or Stockholm.\n\nWe offer you the flexibility to work where you work best! 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