Lead the technical architecture for Spotify's Agent Engine, integrating AI systems and improving agent-based experiences while guiding platform consolidation efforts.
Spotify’s Personalization team is building the next generation of intelligent listening experiences. Across surfaces like DJ, Search, AI Playlists, and Home, we’re evolving from standalone features into a unified, agent-powered platform.
Generative AI is reshaping how we build products and systems. As part of this shift, we’re creating a shared Agent Engine that powers agent-based experiences across Spotify. You’ll join a cross-functional group of engineers, researchers, and product partners working at the intersection of distributed systems, machine learning, and user experience to shape how millions of listeners interact with audio every day.
What You'll Do
- Lead the technical architecture of Spotify’s Agent Engine, the shared runtime that powers agent-based experiences across the platform
- Guide the transition of existing agent-powered features into a unified system, balancing speed, reliability, and real-world product constraints
- Design how internal systems can be exposed as agent capabilities, enabling seamless integration across recommendations, search, catalog, and more
- Build and improve evaluation systems that help teams measure quality, reliability, and user impact with confidence
- Partner with research and machine learning teams to define what belongs in system design versus model capabilities
- Explore and prototype new approaches to agent-based systems, and bring successful ideas into production at scale
- Support best practices in building production-ready AI systems, including experimentation, observability, and performance optimization
- Contribute to technical standards that help teams move faster while maintaining security and reliability
- Stay connected to advances in the AI and machine learning community, and apply relevant ideas to Spotify’s products
Who You Are
- You have experience building and scaling production AI systems, including systems powered by large language models
- You are comfortable working across system design, infrastructure, and machine learning concepts, and enjoy connecting these areas
- You have experience with areas such as agent orchestration, LLM infrastructure, evaluation systems, or data pipelines for machine learning
- You have worked on platform or consolidation efforts that bring multiple systems or teams together
- You are able to make progress in ambiguous problem spaces and bring structure to open-ended challenges
- You communicate clearly and work well with engineering, product, and research partners across different levels of the organization
- You stay informed on developments in AI and are motivated to apply new ideas in practical ways
- You take a pragmatic approach to building, using prototypes and iteration to move ideas forward
- You take ownership of outcomes and proactively manage risks, trade-offs, and expectations
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location
- This team operates within the Eastern Standard time zone for collaboration
The United States base range for this position is $281,196 - $401,709 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, 13 paid flexible holidays, 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 transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
Top Skills
Agent Orchestration
AI
Data Pipelines
Large Language Models
Machine Learning
Similar Jobs
eCommerce
As a Machine Learning Engineer, you'll create and optimize production-ready ML solutions, manage the ML lifecycle, and conduct experiments.
Top Skills:
Large Language ModelsMachine LearningMachine Learning AlgorithmsPersonalizationPythonRecommendationsTransformers
eCommerce
The Senior Machine Learning Engineer will develop and optimize ML infrastructure, create data pipelines, and model orchestration ensuring data quality and performance monitoring.
Top Skills:
AWSDatabricksFeastFlinkPythonRayRedshiftSnowflakeSQL
Productivity • Software • Conversational AI
The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.
Top Skills:
AirflowAWSAzureDockerDynamoDBEmrFlinkGCPJavaKafkaKubeflowKubernetesMetaflowMlflowOpensearchPythonSagemakerSnowflakeSparkSQL
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories



_0.png)