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