Staff Engineer (Content Intelligence Infrastructure)

Requirements

  • You have extensive experience building and scaling large-scale backend and infrastructure systems in distributed environments
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  • You have strong technical judgment and can balance scalability, reliability, cost, and product needs effectively
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  • You have strong programming experience in Java, Python, and/or Scala
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  • You understand the challenges of building systems that process high-volume multimedia or real-time workloads
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  • 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
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  • You are comfortable operating in ambiguous, fast-moving environments and helping shape technical direction from the ground up
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  • You communicate effectively across engineering, product, and leadership stakeholders
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  • You have experience leading complex technical initiatives that span multiple teams or organizational areas
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  • You care deeply about collaboration, mentorship, and creating alignment across teams
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  • Exposure to search infrastructure, recommendation systems, or audio processing systems is a strong plus
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  • Experience working in startup environments or early-stage product areas where ownership and adaptability are critical is highly valued
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  • 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

What the job involves

  • The Experience team designs Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration
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  • Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world
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  • 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
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  • If it touches a consumer, we shape it
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  • We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify
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  • The Content Intelligence Product Area is a core part of Spotify’s Content Platform within the Experience mission
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  • We build systems that create deep, machine-readable understanding of content across audio, video, text, and images before it reaches users
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  • This enables automation, safety, and entirely new product experiences
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  • 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
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  • We’re now looking for a Staff Engineer to help build and scale foundational infrastructure powering content understanding across Spotify
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  • This role sits at the intersection of backend systems, ML infrastructure, distributed data systems, and AI-enabled platform capabilities
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  • 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
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  • Lead the design and evolution of data, backend and ML infrastructure systems powering Spotify’s content intelligence capabilities
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  • Build scalable infrastructure for multimodal content processing across audio, video, text, and image understanding pipelines
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  • Partner closely with Product Managers, Engineering Managers, and senior engineers to shape technical strategy across the Content Intelligence Product Area
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  • Drive architectural decisions across distributed systems, ML infrastructure, data processing platforms, and platform reliability
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  • Improve infrastructure supporting AI and LLM-enabled workflows, including podcast and audiobook transcript processing, metadata enrichment, and content understanding systems
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  • Develop reliable and cost-efficient systems for high-throughput content processing and real-time intelligence use cases
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  • Collaborate across organizational boundaries to drive alignment, technical quality, and long-term platform investments
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  • Mentor engineers and contribute to raising the engineering bar across the organization
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