Sr. AI Transformation Engineer

Roku•San Jose, CA

2d•$242,200 - $486,000•Hybrid

About The Position

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.

Requirements

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

Nice To Haves

built fluency across the agentic engineering toolchain — coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks
show how they've used AI or automation to move faster, raise the bar, and scale their impact
drive an agent, verify its output, and ramp on an unfamiliar codebase with an agent helping you

Responsibilities

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