The Experience team designs 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.
The Content Intelligence Product Area is a core part of Spotify’s Content Platform within the Experience mission. We build systems that create deep, machine-readable understanding of content across audio, video, text, and images before it reaches users. This enables automation, safety, and entirely new product experiences. Our work powers content enrichment, quality analysis, annotation platforms, and scalable intelligence systems that allow teams across Spotify to build without needing direct content understanding expertise.
We’re now looking for a Staff Engineer to help build and scale foundational infrastructure powering content understanding across Spotify. This role sits at the intersection of backend systems, ML infrastructure, distributed data systems, and AI-enabled platform capabilities. You’ll help shape infrastructure strategy across the product area while partnering with senior engineers, product leaders, and cross-functional teams to execute on long-term technical investments.
What You'll Do
Lead the design and evolution of data, backend and ML infrastructure systems powering Spotify’s content intelligence capabilities
Build scalable infrastructure for multimodal content processing across audio, video, text, and image understanding pipelines
Partner closely with Product Managers, Engineering Managers, and senior engineers to shape technical strategy across the Content Intelligence Product Area
Drive architectural decisions across distributed systems, ML infrastructure, data processing platforms, and platform reliability
Improve infrastructure supporting AI and LLM-enabled workflows, including podcast and audiobook transcript processing, metadata enrichment, and content understanding systems
Develop reliable and cost-efficient systems for high-throughput content processing and real-time intelligence use cases
Collaborate across organizational boundaries to drive alignment, technical quality, and long-term platform investments
Mentor engineers and contribute to raising the engineering bar across the organization
Who You Are
You have extensive experience building and scaling large-scale backend and infrastructure systems in distributed environments
You have strong technical judgment and can balance scalability, reliability, cost, and product needs effectively
You have strong programming experience in Java, Python, and/or Scala
You understand the challenges of building systems that process high-volume multimedia or real-time workloads
You have worked with systems and products that use AI and LLMs at large scale and can demonstrate direct experience in building such products. You can demonstrate a good understanding of the quality scale and cost trade-offs of these technologies.
You are comfortable operating in ambiguous, fast-moving environments and helping shape technical direction from the ground up
You communicate effectively across engineering, product, and leadership stakeholders
You have experience leading complex technical initiatives that span multiple teams or organizational areas
You care deeply about collaboration, mentorship, and creating alignment across teams
Exposure to search infrastructure, recommendation systems, or audio processing systems is a strong plus
Experience working in startup environments or early-stage product areas where ownership and adaptability are critical is highly valued
Where You'll Be
This role is based in New York
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.
Skills Required
- Extensive experience building and scaling backend and infrastructure systems
- Strong technical judgment balancing scalability, reliability, cost, and product needs
- Strong programming experience in Java, Python, and/or Scala
- Experience with AI and LLMs at large scale
- Experience leading complex technical initiatives across multiple teams
- Exposure to search infrastructure, recommendation systems, or audio processing systems is a strong plus
Spotify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Spotify and has not been reviewed or approved by Spotify.
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Flexible Benefits — Employees consistently praise the total compensation package beyond base salary, highlighting a mix of RSUs, cash incentives, and stipends alongside core pay. The package is described as flexible and customizable through equity choices (e.g., RSUs, options, cash) that can be tailored for long-term wealth building.
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Leave & Time Off Breadth — Time-off offerings are repeatedly highlighted as substantial, including generous vacation, paid sick days, volunteer time, and flexible holidays. These policies are framed as a meaningful part of the overall rewards experience beyond salary.
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Healthcare Strength — Health coverage is portrayed as comprehensive, spanning medical, dental, vision, life insurance, disability coverage, and mental health support. Additional employer contributions to HSAs are cited as strengthening the overall health and wellness value proposition.
Spotify Insights
What We Do
Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 50m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience.
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