Staff Software Engineer

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. The Role As a Staff Software Engineer on Experimentation Tooling, you will be a senior technical leader responsible for designing and evolving core experimentation infrastructure used by product, editorial, and analytics teams across the organization. This is a hands‑on individual contributor role with significant influence over architecture, technical direction, and engineering standards. You will work on systems that power client‑side, server‑side, and edge experimentation, unify metrics and reporting, and dramatically reduce the time and friction required to launch and analyze tests. You’ll partner closely with product managers, data teams, platform teams, and other senior engineers to scale experimentation safely and effectively. The Daily 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. Requirements 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. Nice To Haves 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. Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal‑opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law. If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit the accessibility page for instructions to submit your request. #J-18808-Ljbffr