Spotify
Personalization
SeniorBackendEngineer-Surfaces/PZN
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Backend Engineer - Surfaces/PZN at Spotify. Skills: experimentation service, agentic workflows, API-first orchestration layers, LLM-driven workflows, experimentation infrastructure. Own and evolve the core experimentation service, building agentic workflows that automate experiment setup, configuration, and validation across multiple backend systems. Design and maintain API-first orchestration layers that coordinate across experimentation and content delivery systems”
What You'll Achieve.
keep millions of users listening by making great recommendations; enable teams to go from a raw hypothesis to a fully configured, running experiment in minutes instead of days
Industry & Context.
Identify, diagnose, and resolve bottlenecks in experiment orchestration
This team operates within the Eastern Standard time zone for collaboration.
What They're Looking For.
Must Have
experience building and operating large-scale backend systems serving high-traffic user experiences, using AI-assisted tools to develop high quality software, experienced with distributed systems, APIs, and service-oriented architecture, design systems with performance, scalability, and reliability in mind, product-minded engineer who thrives at the intersection of infrastructure, AI, and experimentation, translating conceptual architectures into scalable, production-ready code, working across multiple teams and collaborating with cross-functional partners, creating maintainable systems that enable fast iteration and experimentation, turning fragmented, manual processes into elegant, automated workflows, defining and working with SLOs, SLAs, and observability tooling
Nice to Have
LLMs, agent frameworks, or A testing infrastructure is a bonus
What You'll Do.
Own and evolve the core experimentation service
building agentic workflows that automate experiment setup
and validation across multiple backend systems
Design and maintain API-first orchestration layers that coordinate across experimentation and content delivery systems
Build and integrate LLM-driven workflows into robust
production-ready infrastructure
and validator architectural patterns
Define and uphold SLOs and SLAs for experimentation infrastructure
contributing to a culture of reliability and operational excellence
Partner closely with content
and platform teams to scale automated experimentation patterns across a growing range of surfaces and configurations
and resolve bottlenecks in experiment orchestration to ensure fast and reliable workflows
Collaborate across squads to continuously improve how experimentation and evaluation are delivered across Spotify Surfaces
Contribute to architectural decisions that improve system scalability
How You'll Work.
Team & Collaboration
Partner closely with content, feature, and platform teams; Collaborate across squads
Full Job Description
## Description The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we're behind some of Spotify's most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you'll keep millions of users listening by making great recommendations to each and every one of them. The Experimentation and Learning team (SEAL) sits within the Surfaces Foundation product area in the Personalization mission. This team builds the experimentation and learning infrastructure for Spotify Surfaces — powering how we test, evaluate, and ship personalized experiences across Home and beyond. By creating a unified, agent-driven experimentation ecosystem, we enable teams to go from a raw hypothesis to a fully configured, running experiment in minutes instead of days. ## What You'll Do Own and evolve the core experimentation service, building agentic workflows that automate experiment setup, configuration, and validation across multiple backend systems Design and maintain API-first orchestration layers that coordinate across experimentation and content delivery systems Build and integrate LLM-driven workflows into robust, production-ready infrastructure, including planner, generator, and validator architectural patterns Define and uphold SLOs and SLAs for experimentation infrastructure, contributing to a strong culture of reliability and operational excellence Partner closely with content, feature, and platform teams to scale automated experimentation patterns across a growing range of surfaces and configurations Identify, diagnose, and resolve bottlenecks in experiment orchestration to ensure fast and reliable workflows Collaborate across squads to continuously improve how experimentation and evaluation are delivered across Spotify Surfaces Contribute to architectural decisions that improve system scalability, observability, and maintainability ## Who You Are
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