Responsibilities
- Design and build large-scale distributed systems for ingesting, processing, and indexing multimedia content.
- Architect and implement Kubernetes-based microservices handling millions of requests per day with sub-second latency.
- Develop multimedia indexing pipelines that extract audio, video, and metadata features using signal processing and machine learning techniques.
- Integrate agentic AI and LLM capabilities into development workflows and service operations, including automated service recovery.
- Build multi-step production agents that detect regressions, bisect commits, propose fixes, and generate code for review.
- Develop internal tooling, skills, harnesses, and services that improve engineering team productivity.
- Optimize systems for throughput, latency, and cost efficiency across multi-region cloud deployments.
- Implement monitoring, alerting, observability, and distributed tracing solutions.
- Lead technical design reviews and mentor engineers on distributed systems, code quality, and architecture.
- Participate in on-call rotations and drive reliability, performance, cost-reduction, and technical-debt initiatives.
Requirements
- At least 5 years of professional software engineering experience building and operating production systems at scale.
- Strong proficiency in at least one systems programming language such as Python, C++, or Go.
- Experience designing and implementing scalable, reliable, and fault-tolerant distributed systems.
- Strong understanding of data structures, algorithms, and system design trade-offs.
- Experience with AWS or GCP cloud platforms, including compute, storage, networking, and managed services.
- Production experience with Docker and Kubernetes.
- Proficiency with Git, CI/CD pipelines, and modern software development practices.
- Experience integrating large language models such as ChatGPT, Claude, or Cursor into development workflows or production systems.
- Familiarity with agentic AI frameworks and autonomous agent architectures.
- Experience with prompt engineering and LLM optimization, including few-shot learning, chain-of-thought prompting, and retrieval-augmented generation.
- Experience with multimodal AI models processing text, image, audio, and video data.
- Understanding of AI safety practices including content filtering, bias detection, and responsible AI deployment.
- Strong problem-solving, debugging, communication, and technical explanation skills.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Benefits
- Hybrid work generally consists of Monday through Thursday in the office, with Fridays generally flexible for remote work unless the role or location requires five days onsite.
- Benefits may include healthcare, life, accident, disability, commuter, retirement options, mental health and financial wellness support, and paid time off, subject to location and role eligibility.
- Reasonable accommodations are available in accordance with applicable law.
Tech Stack
Categories
About Roku
With the #1 platform for streaming television in the U.S., Roku wants to revolutionize the way the world watches TV. Our Roku-branded TVs, Roku TV models, Smart Home system, streaming players, audio equipment, and the purpose-built operating system that powers it all can turn any home into a home theater, with seamless integration of hardware and software. Our commitment to our users extends to our brand studio, which creates innovative Roku Originals exclusively for The Roku Channel, a free channel that reaches approximately 80 million households in the U.S. and Mexico. Join us and you'll have the chance to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines. Be a part of shaping the future of streaming at weareroku.com.