Sr. AI Transformation Engineer

About the role

Roku is seeking a Senior AI Transformation Engineer to join the AI Enablement Team and drive end-to-end delivery of agentic AI systems that measurably transform how work gets done across Roku. In this role, you will embed directly with business and technical teams — including Legal, FP&A, Accounting, Brand, Customer Support, and Engineering — to discover the highest-value opportunities for AI-powered automation and deliver production-grade solutions. You will own the full lifecycle from opportunity identification and scoping through system design, build, deployment, and adoption, operating as a self-directed contributor who thrives in ambiguity and can navigate complex organizational dynamics. This is a hands-on builder role that requires strong software engineering fundamentals, deep AI expertise, and a product-oriented mindset focused on adoption and measurable business impact, not demos. You will go beyond point solutions to reimagine how entire functions operate as AI-native, agent-powered systems, and you will codify reusable patterns back into Roku's broader AI platform strategy. The ideal candidate brings technical depth, cross-functional collaboration skills, and the ability to drive change management that ensures the solutions you build are trusted and actively used.

What are the responsibilities of the role?

• Drive AI deployments from discovery and scoping through system design, build, and production rollout, owning the outcome end to end
• Embed directly with business and technical teams to diagnose real problems, often before they are clearly articulated, and identify the highest-value opportunities for agentic automation
• Prepare clear scopes of work and pragmatic project plans for both prototypes and full production deployments, making real-time trade-offs on scope, priority, and quality
• Design, build, test, and deploy production-grade agentic AI applications and integrations, moving from prototype to live system in short cycles
• Reimagine how entire functions operate as AI-native, agent-powered systems, going beyond individual task automation
• Connect solutions to Roku's data platforms, internal systems, and enterprise APIs, working across complex and disparate data sources, pipelines, and metric layers
• Lead onboarding, enablement, and change management for the teams you serve, iterating on real user feedback until solutions are trusted and actively used
• Define and track success through production adoption, workflow impact, and measurable business value
• Collaborate with embedded AI Ambassadors, mentor teammates, and flex across functions, domains, and initiatives as priorities evolve
• Codify reusable patterns and field learnings back into Roku's broader AI platform strategy to strengthen shared capabilities and frameworks

We're Excited If You Have

• 5+ years of software engineering, full-stack engineering, or technical deployment experience with a track record of shipping production systems
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Strong software engineering fundamentals with the ability to write and ship production-grade code (e.g., Python and/or JavaScript/TypeScript)
• Hands-on experience building or deploying systems powered by LLMs, generative models, or agentic frameworks
• Demonstrated ability to thrive in ambiguity, decomposing open-ended problems into workstreams and making sound trade-offs under pressure
• Proven experience working directly with non-technical teams and stakeholders, translating business needs into technical solutions and communicating clearly to executive audiences
• A track record of building solutions that achieve adoption and measurable impact
• Strong product sense and a bias toward outcomes over output
• High autonomy and ownership with the ability to drive decisions and deliver independently in fast-moving environments
• Experience with modern AI engineering patterns such as RAG, prompt engineering, agent orchestration, tool-use, human-in-the-loop controls, model evaluation, and MLOps/LLMOps
• Familiarity with cloud platforms (AWS, Azure, or GCP), containerization (Docker/Kubernetes), and CI/CD practices
• Experience with modern data architectures and relational databases