Engineering Manager AI Fleet Management & Honk

Spotify's Platform team develops infrastructure, tooling, frameworks, and capabilities to support rapid growth and scalability, impacting millions of developers and users worldwide. The team focuses on creating systems that enable quick learning and easy scaling of the platform.

Location: EMEA region, within the Central European and GMT time zones, excluding France.

Responsibilities

• Lead and grow a team building AI-native backend systems that orchestrate large-scale, autonomous fleet changes
• Define the technical vision for integrating LLM-powered reasoning and agent-based execution into production infrastructure
• Architect systems where AI agents analyze service metadata, generate safe change plans, execute updates, and validate outcomes
• Establish safety boundaries, evaluation frameworks, and observability models for AI-driven automation at scale
• Drive responsible AI adoption by embedding governance, auditability, and human-in-the-loop safeguards into system design
• Balance rapid experimentation with platform reliability, ensuring intelligent automation meets production-grade standards
• Partner with product and go-to-market teams to position Portal and AI fleet management as a leading developer platform
• Build a team culture grounded in curiosity, technical rigor, and continuous learning in emerging AI systems

Requirements

• 3+ years of experience leading engineering teams working on distributed systems or developer platforms at scale
• 5+ years of experience in backend engineering with strong expertise in Java, Python, and/or Node.js
• Experience integrating AI/ML systems, LLMs, agent frameworks, or AI-assisted tooling into real-world systems
• Understanding of how autonomous systems make decisions and how to design guardrails that ensure safety, reliability, and traceability
• Systems thinking, considering data flows, model behavior, orchestration layers, and operational impact
• Comfort in leading in emerging technical domains where patterns are still forming
• Ability to create inclusive environments where diverse perspectives strengthen technical and product decisions
• Effective communication across engineers, product leaders, and executives about AI opportunities and risks