Company

Experience

StaffEngineer-ContentIntelligenceInfrastructure

London, United Kingdom; Stockholm, Sweden Permanent Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Staff Engineer - Content Intelligence Infrastructure. Skills: ML infrastructure, data processing, distributed systems, AI/LLM workflows. Lead design and evolution of infrastructure systems. Build scalable infrastructure for multimodal content processing”

Industry & Context.

Experience

What They're Looking For.

Must Have

extensive experience building and scaling large-scale backend and infrastructure systems in distributed environments, technical judgment, programming experience in Java, Python, and/or Scala, understanding of the challenges of building systems that process high-volume multimedia or real-time workloads, worked with systems and products that use AI and LLMs at large scale, demonstrate direct experience in building such products, good understanding of the quality scale and cost trade-offs of these technologies, comfortable operating in ambiguous, fast-moving environments, helping shape technical direction from the ground up, communicate effectively across engineering, product, and leadership stakeholders, experience leading complex technical initiatives that multiple teams or organizational areas, care deeply about collaboration, mentorship, and creating alignment across teams

Nice to Have

Exposure to search infrastructure, recommendation systems, or audio processing systems, Experience working in startup environments or early-stage product areas where ownership and adaptability are critical

What You'll Do.

Lead design and evolution of infrastructure systems

Build scalable infrastructure for multimodal content processing

Shape technical strategy across Content Intelligence

Drive architectural decisions

Improve infrastructure supporting AI/LLM workflows

Develop reliable and cost-efficient systems

Collaborate across organizational boundaries

Contribute to raising engineering bar

How You'll Work.

Team & Collaboration

Partner closely with Product Managers, Engineering Managers, and senior engineers; Collaborate across organizational boundaries to drive alignment; creating alignment across teams

Communication Scope

communicate effectively across engineering, product, and leadership stakeholders

Full Job Description

## 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 initia

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