.png)
Design, build, and operate secure enterprise AI platform capabilities connecting models, agents, and internal systems. Own major infrastructure workstreams (MCP gateway, enterprise context), build backend services and APIs, enable identity-aware governance (access, permissions, auditing), design agentic workflows, and take operational ownership while partnering with stakeholders to scale dependable AI tooling across Spotify.
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.
The United States base range for this position is $164,448–$234,926 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
Spotify San Francisco, California, USA Office
San Francisco, United States
Similar Jobs
Cloud • Fintech • Food • Information Technology • Software • Hospitality
Build and optimize automated release engineering systems, including CI/CD pipelines, build and deployment tooling, and AWS cloud infrastructure. Ensure software delivery quality, security, compliance, and reliability. Lead complex projects, participate in on-call support, mentor teammates, and promote technical excellence. The role uses Go, Java/Kotlin, TypeScript, GitHub Actions, PostgreSQL, DynamoDB, Backstage, AWS, and AI development tools.
Top Skills:
AWSBackstageCi/CdClaude CodeDynamoDBGithub ActionsGoJavaKotlinPostgresTypescript
Artificial Intelligence • Healthtech • Logistics • Social Impact • Software • Telehealth
Supports clinical leaders by managing workforce tracking, payroll compliance follow-up, documentation review, reporting, training and compliance tracking, escalation workflows, audits, and operational documentation. The role maintains dashboards and trackers, prepares workforce reports, supports workflow launches, identifies process inefficiencies, and routes non-clinical issues. It is a remote administrative operations role with no clinical, patient-facing, care coordination, disciplinary, or performance-management responsibilities.
Top Skills:
Ehr SystemsGoogle SuiteRipplingSlack
Information Technology • Productivity • Software • Infrastructure as a Service (IaaS)
Develop and scale NinjaOne’s ticketing and billing products using Java and Kotlin. Design reliable enterprise software, REST services, relational data systems, caching solutions, and client-server applications. Address scalability, asynchronous design, API development, testing, and integrations with accounting platforms such as QuickBooks and Xero. Contribute hands-on code, apply object-oriented design principles, and help ship software serving millions of endpoints.
Top Skills:
AWSC++GoJavaJerseyKotlinPostgresRedisRestSpring
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
