Senior Software Engineer - Enterprise AI

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.