Software Engineer, Roku

• Bachelor’s or master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science, or a related technical field
• 2+ years of experience in software engineering, AI/ML engineering, backend development, or adjacent domains, with strong software engineering fundamentals and the ability to build production-grade systems
• Strong proficiency in Python, plus experience with C/C++ or another systems language
• Hands-on experience with LLM-based systems, including prompt design, retrieval, tool use, memory handling, and agent orchestration patterns
• Experience building and maintaining RAG pipelines, agent frameworks, MCP servers or equivalent function-calling architectures, and conversational interfaces
• Familiarity with cloud platforms, REST APIs, containerization, and modern deployment environments
• Experience with observability, evaluation, experimentation, and feedback loops for AI systems in production
• Ability to work independently, manage ambiguity, move quickly, and deliver incrementally in a fast-paced environment
• Excellent communication skills, sound engineering judgment, and a collaborative working style

Desirable

• We are looking for a hands-on, systems-oriented Agentic AI Engineer to design, build, and maintain intelligent agents and copilots that drive automation, accelerate workflows, and unlock new product and platform capabilities for Roku TV
• You will own the full lifecycle of agent development—from prototyping and architecture through orchestration, evaluation, deployment, observability, and continuous improvement
• You will contribute directly to Roku’s AI strategy by engineering reusable components, optimizing agent workflows, and ensuring strong real-world performance in production environments
• Architect, develop, and deploy AI agents and copilots for Roku TV use cases, integrating them with internal systems, tools, and services
• Own end-to-end agentic systems from concept to production, including model selection, prompt and context design, retrieval strategies, backend services, and conversational interfaces
• Design and implement single-agent and multi-agent orchestration patterns, including handoffs, delegation, and cooperative task execution
• Build scalable RAG and context pipelines that provide high-quality grounding for AI systems and keep them aligned with evolving data sources and business logic
• Implement tool-calling, function-calling, and MCP-style integrations so agents can safely take actions and interact with the systems around them
• Create reusable agent templates, modular components, and paved-path patterns that accelerate adoption across teams and use cases
• Establish strong evaluation, observability, and monitoring for conversation quality, task success rate, latency, cost, and overall system performance
• Build safeguards that improve production readiness and reliability, including testing pipelines, controlled rollouts, drift detection, and mechanisms that prevent error amplification in multi-step workflows
• Prototype quickly, run experiments, and translate successful ideas into durable, scalable software solutions
• Partner closely with engineering, product, QA, infrastructure, and cross-functional teams to deliver meaningful business and customer outcomes