Staff Software Engineer

Welcome to Warner Bros. Discovery... the stuff dreams are made of.

Who We Are...

When we say, "the stuff dreams are made of," we're not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD's vast portfolio of iconic content and beloved brands, are the storytellers bringing our characters to life, the creators bringing them to your living rooms and the dreamers creating what's next...

From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.

The Team

The Experimentation Tooling team builds the platforms, services, and workflows that enable fast, reliable, and scalable experimentation across CNN's digital products. Our mission is to make experimentation easy, frictionless, and effective-so teams can quickly validate or invalidate hypotheses without heavy engineering overhead. We are addressing challenges such as fragmented tooling, slow and manual testing workflows, limited self-serve capabilities, and unclear ownership across vendors and in-house solutions. The team is building a centralized, vendor-agnostic experimentation platform that supports multiple surfaces (Web, iOS, Android, CTV), prioritizes performance and data integrity, and treats internal tooling as a product with real customers.

• Lead technical design and architecture of core experimentation services and platforms, with a focus on scalability, reliability, and low latency.
• Build and evolve a centralized, vendor-agnostic experimentation platform, enabling multiple teams and products to run experiments consistently across surfaces.
• Enable edge and server-side testing capabilities to expand experimentation options while minimizing performance impact on end users.
• Champion data integrity and measurement excellence, helping design systems that surface source-of-truth metrics and automate experiment analysis and reporting.
• Reduce friction and increase velocity by automating experimentation workflows from ideation through results, enabling more concurrent and higher-quality tests.
• Act as a technical mentor and force multiplier, raising the bar for engineering quality, design rigor, and operational excellence across the team.
• Collaborate cross-functionally with product, editorial, analytics, and platform partners to ensure experimentation tooling meets real-world needs and is widely adopted.
• Model platform-as-a-product thinking, measuring success through adoption, reliability, performance, and impact-not just feature delivery.

• Deep experience designing and building distributed systems or platform services used by multiple teams.
• Strong background in backend engineering (e.g., APIs, data pipelines, services), with comfort working across client, server, and edge environments, especially Node.JS, as well as frontend engineering, including TypeScript, JavaScript, and frameworks such as Vue or React.
• Proven ability to design performant, low-latency systems that operate at scale.
• Experience working with experimentation, feature flagging, analytics, or data platforms (vendor or in-house).
• Solid understanding of data quality, observability, and measurement in production systems.
• Ability to set technical direction for complex problem spaces and guide architecture decisions beyond your immediate team.
• Comfort navigating ambiguous, cross-cutting challenges that span teams, vendors, and platforms.
• Strong written and verbal communication skills, especially when explaining technical tradeoffs to non-engineering partners.
• A track record of influencing without authority and driving alignment across senior stakeholders.
• Familiarity with edge compute, CDN-based architectures, or server-side experimentation.
• Experience integrating and optimizing deployment pipelines (CI/CD)
• Fluent in English

• Exposure to media, content, or consumer-scale digital products.
• Interest in applying AI or automation to accelerate experimentation workflows.
• Kafka
• Go
• Rust
• Content Management Systems