The Platform team creates the technology that enables Spotify to learn quickly and scale easily, enabling rapid growth in our users and our business around the globe. Spanning many disciplines, we work to make the business work; creating the infrastructure, tooling, frameworks, and capabilities needed to welcome a billion customers.
Enterprise AI builds and operates the internal AI platform layer that supports Spotifiers across the company. We’re helping evolve AI tooling into reliable infrastructure that teams can use in their day-to-day work. Our team builds the connective tissue between AI models and Spotify’s internal systems, with a focus on secure access, governance, identity, integrations, and dependable AI infrastructure.
What You'll Do
- Design, build, and operate secure enterprise AI platform capabilities that connect AI models, agents, tools, and Spotify’s internal systems.
- Own major workstreams across our enterprise AI infrastructure, including our Model Context Protocol (MCP) gateway and enterprise context capabilities, from technical design through launch and operation.
- Build reliable backend services, APIs, and integrations that enable AI-powered experiences across Spotify’s digital workplace.
- Help develop scalable approaches to AI governance, including identity-aware access, permissions, auditing, policy enforcement, and managing risks associated with third-party AI-enabled tools.
- Design, build, test, and evaluate agentic systems and workflows that help Spotifiers access information and accomplish tasks effectively.
- Take operational ownership of the services and components you build, balancing speed, reliability, security, and long-term maintainability.
- Partner with engineers and stakeholders across Spotify to identify opportunities, make thoughtful technical tradeoffs, and turn emerging AI needs into scalable platform capabilities.
- Contribute to engineering practices, knowledge sharing, and AI fluency as we learn how to operate enterprise AI infrastructure at Spotify scale.
Who You Are
- You have strong software engineering fundamentals and experience building, testing, debugging, and operating reliable backend systems.
- You are experienced with backend languages such as Python, Go, or similar and are comfortable designing APIs and integrations across complex systems.
- You understand software architecture and how services, APIs, enterprise tools, and user-facing experiences fit together.
- You have experience with identity and authentication concepts and technologies such as OAuth, SAML, or SCIM.
- You have experience working with cloud infrastructure; familiarity with Google Cloud Platform is valuable.
- You are comfortable navigating ambiguity, creating clarity, and independently making thoughtful technical tradeoffs.
- You care about operational ownership and building dependable infrastructure that other teams and employees can rely on.
- You enjoy experimentation, iteration, knowledge sharing, and continuous learning in a collaborative engineering environment.
- Experience with enterprise SaaS or platform engineering, or with LLM integration patterns such as tool use, function calling, agentic workflows, or systems-level prompt engineering, will help you make an impact in this role.
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
- Strong software engineering fundamentals with experience building, testing, debugging, and operating reliable backend systems.
- Experience with backend languages such as Python, Go, or similar and designing APIs and integrations.
- Understanding of software architecture and integration of services, APIs, enterprise tools, and user-facing experiences.
- Experience with identity and authentication technologies such as OAuth, SAML, or SCIM.
- Operational ownership of services, balancing speed, reliability, security, and maintainability.
- Experience working with cloud infrastructure; familiarity with Google Cloud Platform (GCP).
- Experience with enterprise SaaS or platform engineering and LLM integration patterns (tool use, function calling, agentic workflows, systems-level prompt engineering).
- Ability to navigate ambiguity, make technical tradeoffs, collaborate cross-functionally, and share knowledge.
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
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