Senior Backend Engineer - Podcast

The Podcast Mission develops strategies and builds products that serve creators and listeners interested in podcast and video content. As the #1 podcast platform in the world, we look to continue improving and scaling the experience of podcasts on Spotify. We build and maintain products like Spotify for Podcasters, Megaphone, and Chartable, and are always eager to provide creators with easy ways to increase their audiences on Spotify and give them new innovative means for monetization.

Midas owns the Spotify for Creators systems that help podcast creators control and enrich how their content appears on Spotify. We build creator-facing surfaces and backend services for merchandising asset features like transcripts, chapters, clips, previews, and more - giving creators the ability to manage how these assets are presented across Spotify.

Our scope is expanding into a new generation of personalized podcast experiences. We recently introduced a system that generates brief, personalized podcast episodes for listeners based on their context and the world around them. As part of the team, you’ll help evolve these early generated-content experiences into durable, production-grade systems that can scale to millions of listeners and creators worldwide.

Lead the design and evolution of backend services that generate, distribute, and support personalized podcast episodes at scale

Help transform MVPs and prototypes into reliable production systems with clear APIs, durable data flows, strong observability, and thoughtful operational patterns

Shape the technical direction for agentic workflows and help establish quality and reliability standards for AI-generated content systems

Build and improve creator merchandising features in Spotify for Creators, including podcast chapters, transcripts, previews, clips, guests, topics, thumbnails, and more

Collaborate with engineers, product managers, designers, and cross-functional stakeholders across Spotify missions to align on requirements and deliver integrated experiences

Partner closely with product and design to iterate on ideas, unblock technical exploration, and make pragmatic tradeoffs that balance experimentation with long-term maintainability

Mentor engineers across the team and help raise the quality of technical design discussions, RFCs, reviews, and operational practices

Contribute to a culture of experimentation, ownership, collaboration, and continuous learning

You have 5+ years of experience building and operating production backend systems using Java, Kotlin, Scala, Go, or similar languages

You are experienced with distributed systems concepts including asynchronous processing, queues/pub-sub systems, idempotency, service-to-service APIs, storage design, failure handling, and observability

You have hands-on experience with, or strong curiosity about, LLM-powered applications and agentic workflows

You know how to navigate ambiguity while maintaining strong engineering discipline and production reliability

You care deeply about the user experience for creators and listeners, not just the technical implementation

You communicate clearly across technical and non-technical audiences and collaborate effectively across teams

You have experience mentoring engineers and helping teams improve engineering quality and operational maturity

You care about building inclusive, maintainable systems and collaborative team environments

We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location.

This team operates within the Eastern Standard time zone for collaboration.

The United States base range for this position is $164,448 - $234,926 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays. This range encompasses multiple levels. Leveling is determined during the interview process. Placement in a level depends on relevant work history and interview performance. These ranges may be modified in the future.