eightfold
Distributed Systems Engineer 5 - Membership & Monetization Platform
Netflix
Remote, USA
Full-time
Senior · 9+ years experience
Remote
USD 388000-619000 yearly / year
Discovered 1 weeks ago
JavaKotlinC#ScalaElasticsearchKafka
Free
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Who We Are
Every Netflix membership, from the moment someone signs up to every plan change, renewal, and cancellation flows through our platform. The Membership & Monetization Platform (MMP) team owns the commerce backbone of Netflix: the Tier 0 services that manage subscription state, pricing, and plan availability for ~330 million members across 190+ countries, handling millions of requests per second.
We're a team of engineers who care deeply about correctness at scale, building systems where getting it wrong means real revenue impact. Our platform is the foundation for Netflix's biggest commercial bets, from Ads and Games to Live Streaming.
What You Will Work On
You'll work across the full spectrum, from product-facing features that directly impact acquisition and retention, to the platform infrastructure that makes them possible at Netflix scale.
You'll partner with product managers, designers, and data scientists to build commerce experiences that drive growth. Recent examples: our systems enabled the password-sharing crackdown , helped launch the Ads-supported plan , and enabled new features for premium members .
On the platform side, you'll tackle distributed systems challenges: race conditions, consistency guarantees and throughput optimization. You’ll evolve our infrastructure to keep pace with Netflix's expanding commerce surface (Ads, Games, Live Streaming). You'll also be part of the on-call rotation for these Tier 0 services, owning production reliability end-to-end.
We're Eager to Talk to You If:
You have 9+ years of experience building resilient, high-scale, low-latency distributed systems in production.
You've dealt with hard correctness problems: race conditions, eventual consistency, distributed transactions.
You have a platform mindset: You can take vague business directives and translate them into scalable and maintainable solutions.
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