Backend Engineer - Podcast
Role details
Job location
Tech stack
Job description
- 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
Requirements
- 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 Bonus Points
- Experience with Python, prompt iteration and evaluation, tool use, or production AI workflows
- Experience with GCP, GKE, Cloud SQL/Postgres, BigQuery, Bigtable, GCS, or Grafana
- Experience productionizing research projects, prototypes, or experimental systems
- Familiarity with podcast ecosystems, creator tooling, merchandising assets, or personalization systems
- Experience working on content quality, recommendation, or generated media systems
Benefits & conditions
- 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. Go ad-free with Premium ×, * 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.