Software Engineer (Embedded Agentic AI)

Join Roku as a Software Engineer specializing in Embedded Agentic AI. In this role, you will design, build, and maintain intelligent agents and copilots that drive automation and enhance workflows for Roku TV. You will be responsible for the entire lifecycle of agent development, from prototyping to deployment and continuous improvement. You will also contribute to Roku's AI strategy by engineering reusable components and optimizing agent workflows. This position offers a range of benefits, including medical, wellness, and financial benefits, unlimited paid time off, and work-from-home opportunities.

• Concevoir, construire et maintenir des agents intelligents et des copilotes qui automatisent les workflows et débloquent de nouvelles capacités.
• Contribuer directement à la stratégie d'IA de Roku en ingénierie des composants réutilisables, en optimisant les workflows des agents.
• Posséder l'ensemble du cycle de vie du développement des agents, de la prototypage à la production, y compris la sélection des modèles et la conception des prompts.
• Experience with observability, evaluation, experimentation, and feedback loops for AI systems in production
• Hands-on experience with LLM-based systems, including prompt design, retrieval, tool use, memory handling, and agent orchestration patterns
• Bachelor’s or master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science, or a related technical field
• Strong proficiency in Python, plus experience with C/C++ or another systems language
• 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
• Familiarity with cloud platforms, REST APIs, containerization, and modern deployment environments
• 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
• Experience building and maintaining RAG pipelines, agent frameworks, MCP servers or equivalent function-calling architectures, and conversational interfaces
• Experience with multi-agent frameworks or orchestration systems such as LangChain, AutoGen, or Semantic Kernel
• Experience with video, audio, TV, or edge-device environments, especially where latency, cost, and hardware constraints matter
• Familiarity with ML/DL frameworks such as PyTorch or TensorFlow
• Research experience, paper implementation experience, or a habit of applying emerging GenAI techniques pragmatically to real problems