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Senior Software Engineer - Content Platforms Engineering

Tubi - Canada
CompanyTubi - Canada
CategoryEngineering
LocationToronto
RemoteHybrid
EmploymentNot stated
LevelSenior
SalaryNot stated by the employer
Posted1 Jun 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
About the Role: Tubi's content platform is the engine behind one of the largest free streaming services in the world. Every play, every deal, every creator, every frame of video flows through systems CPE owns, and the surface area is enormous. Distributed services running on the hottest path of Tubi's traffic. Video pipelines processing one of the largest workloads in streaming. Workflow engines automating the operations that used to consume entire teams. Creator-facing products turning a back-office process into a real platform. And on top of all of it, an AI-native rebuild of the CMS that most companies aren't willing to attempt. This isn't a single-domain role. It's a platform where backend, frontend, video, infrastructure, and applied AI all collide at the scale where decisions actually matter, where an architectural choice ripples across millions of titles and billions of requests, and where the difference between "good enough" and "great" shows up in revenue. We're looking for builders who want to range across domains — backend one quarter, frontend the next, applied AI the one after that — and who want their work to be felt: by viewers when a title plays instantly, by creators when they go live the same day, by Content Ops when a workflow runs itself, and by the business when the platform stops being a cost center and starts being a force multiplier. The infrastructure is already there. The mandate is already there. What's missing is the people who want to build the thing, not talk about it. Come build it. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto   office two days/week.  What You'll Do: You'll work on systems that sit at the heart of Tubi's business, where the content pipeline meets the viewer, the creator, and increasingly, the AI agent. The work spans the full stack of a modern content platform: distributed services, video infrastructure, workflow automation, and applied AI, all running at the scale of one of streaming's largest free platforms. You'll partner with the Video Team, Content Operations, Business Affairs, Ad Tech, and external creators and studios to build the systems that move Tubi forward: Power seamless content ingestion from partners and creators, turning a sprawling, manual onboarding flow into a self-serve experience that scales with the catalog. Run one of streaming's largest video processing workloads, transforming raw partner files into the optimized formats that play on every Tubi-supported device. Automate the content lifecycle end to end across deal intake, avail creation, metadata review, QC, policy setup, and expiry, replacing manual click-through work with intelligent workflows. Build the content data model and the high-throughput, low-latency services that sit on the hottest path of Tubi's stack, where every play button request lands. Push the boundary of AI-native operations, designing pipelines and APIs where AI agents are first-class operators of the platform, not bolt-on features, and where content intelligence feeds directly into brand-safety, contextual ads, and portfolio decisions. Drive down the cost of streaming at scale, from cloud infrastructure to AI processing, through architectural decisions that compound across millions of titles and billions of requests. Craft production-grade frontends for creators, partners, and Content Ops, where every interaction either earns Tubi a new title or moves an existing one closer to viewers. The UI is not a wrapper around APIs; it's the surface where humans and AI agents collaborate on running the platform. Key Responsibilities: Develop and enhance distributed systems for high availability, scalability, and operability. Design content data models and gRPC APIs that serve UIs, AI agents, and downstream services as first-class clients. Integrate LLMs and ML pipelines into content workflows (metadata enrichment, image/video
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