What You'll Do

Test Strategy & Quality Planning

• Define and own Tubi's multi-platform automation strategy — covering Web, iOS, Android, CTV (Roku, Fire TV, Apple TV, Smart TVs, game consoles), and API layers.
• Establish testing standards, coverage targets, and quality gate policies across the CI/CD pipeline to protect release confidence and production reliability.
• Design specialized test strategies for business-critical scenarios: video playback (HLS/DASH), ad insertion, content recommendation surfaces, and user authentication flows.
• Use AI-assisted analysis (e.g., failure pattern clustering, test gap detection) to continuously improve test strategy based on real production signal and defect trends — not gut instinct.
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Automation Framework & Infrastructure

• Lead the design and maintenance of scalable, cross-platform automation frameworks built for Tubi's unique device matrix and streaming use cases.
• Ensure automation suites are reliable, fast, and integrated as quality gates in CI/CD — owning execution health, not just test coverage numbers.
• Continuously build and evolve AI-augmented engineering workflows/system that fundamentally change how the team creates, maintains, and improves automation — going beyond adopting existing tools to designing new patterns, custom integrations, and repeatable practices that raise the team's output ceiling.
• Own the team's AI capability growth: identify high-leverage AI applications in the automation lifecycle (e.g., AI-assisted test case generation, intelligent flaky cases detection, regression root cause summarization), prototype them, and codify them into team standards.
• Evaluate and selectively adopt emerging testing tools and AI-for-testing innovations. Translate promising external ideas into concrete, team-specific workflows, and make sure adoption leads to measurable improvements in speed, reliability, and engineering quality.
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Team Leadership & Growth

• Manage and grow a team of automation engineers: set clear individual goals, run regular 1:1s, create concrete career development plans, and hold a high bar for technical execution.
• Actively mentor engineers on AI-augmented engineering practices — including prompt engineering, AI-assisted debugging, and responsible review of AI-generated code — so that AI becomes a multiplier, not a shortcut.
• Drive consistent AI tool adoption across the team; share workflows and learnings org-wide to spread impact beyond the immediate team.
• Foster a culture of continuous improvement: encourage experimentation, normalize blameless retrospectives, and track team health alongside delivery metrics.
• Stay current on AI technology trends — proactively surface relevant tools, research, and practices to the team and translate them into actionable process improvements.
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