Full Stack Software Engineer 4 - Localization Engineering

At Netflix, localization isn't simply about translation. It's how we make stories feel native to audiences around the world. Every subtitle, dub, title treatment, artwork, and localized experience helps millions of members connect with content in their own language and culture. Critically, localization is not downstream of Netflix's content pipeline — it is inside it. Content cannot play for international audiences until it is localized.

The Logistics Management squad is the operational backbone of Netflix's localization platform. We own the tools, workflows, and infrastructure that order, track, and fulfill every piece of content.

The team is reimagining how localization works at Netflix. We build the platforms, products, and innovations that enable translation, cultural adaptation, and localization workflows at a global scale. You'll own some of the team's most ambitious initiatives from concept through launch. You'll define how work gets done, create clarity in ambiguity, and partner across engineering, product, design, and business to drive alignment, navigate tradeoffs, and deliver meaningful business outcomes.

We're especially excited to meet people who have built AI-native products and agentic workflows. This includes designing systems where humans remain in the loop and workflows are orchestrated reliably at scale. Experience with durable workflow orchestration, event-driven architectures, distributed systems, and resilient automation is highly valued. You'll help shape platforms that can reason, coordinate, recover from failures, and continuously improve while operating reliably in production. This is an opportunity to rethink how agents, workflows, automation, and human expertise come together so Netflix can deliver world-class localized experiences to members around the globe.

Qualifications

• Deep experience building complex, high-quality user interfaces with HTML, JavaScript/TypeScript, and CSS, with expert-level proficiency in React and modern frontend architecture (component design, state management, performance optimization)

• A strong eye for UI/UX craft. You build interfaces that are clear, predictable, and hold up reliably for enterprise users who rely on them daily

• Experience designing and consuming GraphQL and/or RESTful APIs to power rich client experiences, and comfortable working across the stack, including services built in Java or similar OO languages

• A proven track record of building resilient, high-scale, low-latency services in production, and translating business requirements into technical designs and data models

• Work cross-functionally with design, product, and engineering partners to build, test, deploy, and launch UIs that operationalize our localization workflows at scale

What Sets You Apart

• You’re a self-starter who takes initiative and drives work forward without needing significant direction

• You proactively use AI tools to accelerate your workflow, learn faster, and amplify your impact

• You communicate clearly and are comfortable navigating ambiguity. You ask the right questions, seek out the right context, and make good judgment calls without complete information

• You are product-minded. You're curious about the "why" behind what you're building, and you bring your own ideas and opinions to the table rather than just implementing a spec as given

• You take a thoughtful, practical approach to problem-solving that considers tradeoffs and avoids over-engineering

• You take an interest in how people actually use what you build, and look for ways to get early feedback and validate your work rather than shipping and moving on

• You evangelize new ideas and exemplify technical leadership with a bias for action.

• You appreciate the complexity of engaging with a global challenge, and are passionate about crafting interfaces that feel native, no matter the language or locale

• You are a resourceful engineer who can independently identify the root cause of issues and implement dependable, maintainable solutions across the entire stack

Bonus Points

• Experience applying AI in production systems, e.g., integrating LLMs into user-facing or internal tools and able to identify where applied AI can meaningfully improve workflows