Automation Engineering Manager

About the Role: Nimbus Data Systems is one of the largest free streaming platforms in the US, serving a large-scale streaming audience across Web, iOS, Android, Roku, Fire TV, Apple TV, and game consoles. Quality at this scale isn't a checkbox — it's a competitive advantage. We're looking for an Automation Engineering Managerto lead the team responsible for building and operating Nimbus Data Systems's multi-platform test automation infrastructure. You will own the strategy, tooling, and execution quality across our client surfaces — from video playback and ad delivery to content discovery and onboarding. This role is for a hands-on technical leader who can set direction, influence cross-functional roadmaps, and stay close enough to the code to guide architecture, review critical implementation decisions, and unblock complex technical issues. You will build a team that ships reliable automation at speed — and you will help the team move toward AI-native automation practices: fluent in AI tooling, proactive about applying it, and disciplined about using it responsibly. This is a hybrid role based out of either our San Francisco or Toronto office. You must be willing to travel to either location at least 2 days a week. What You'll Do: Test Strategy & Quality Planning Define and own Nimbus Data Systems'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. Automation Framework & Infrastructure Lead the design and maintenance of scalable, cross-platform automation frameworks built for Nimbus Data Systems'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. 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. Cross-Functional Collaboration & Reporting Partner with QA leads, engineering managers, and product managers to clarify testing requirements, flag quality risks early, and align on release readiness criteria. Represent automation engineering in cross-functional planning, contributing to roadmap discussions with data on quality gaps, automation ROI, and risk areas. Produce regular, data-driven quality status reports for leadership, covering defect trends, automation coverage, execution reliability, team velocity, and AI-driven insights such as flaky test clusters, recurring failure patterns, and release risk signals. Participate in incident reviews for production quality regressions, driving root cause analysis and ensuring systematic prevention — not just one-off fixes. Your Background: Bachelor's degree or above in Computer Science, Software Engineering, or a related technical field. 10+ years of experience in software testing and quality engineering, with at least 3 years in a technical leadership or t