{
  "job_id": "qTVautC8m7C48wxrAAAAAA==",
  "job_city": "Cambridge",
  "job_state": null,
  "job_title": "Software Engineer Intern, Observability in Cambridge",
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  "job_country": "GB",
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  "employer_name": "Roku",
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  "job_posted_at": "11 days ago",
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  "job_description": "Are you looking to start your career as a Software Engineer Intern, Observability in Cambridge? Roku is currently hiring local talent for this position!\nSummary\n\nRoku is seeking an intern to join their observability team to contribute to building the next generation of AI-enhanced observability platform. This 12-week paid internship starts in Summer 2026.\nTeamwork makes the stream work.\n\nRoku is changing how the world watches TV\n\nRoku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers.\n\nFrom your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines.\n\nAbout the role\n\nAre you eager to dive into the world of observability and contribute to building the next generation of Roku's AI-enhanced observability platform? Are you excited to learn about or expand your knowledge of the CNCF open-source ecosystem, including tools for metrics, logs, and tracing, while exploring how AI and Large Language Models can revolutionize observability workflows? Do you enjoy problem-solving, working collaboratively with other teams, and exploring innovative ways to improve their observability experience through intelligent automation? In this role, you'll have the opportunity to grow your skills while helping manage large-scale operations involving high-volume data and requests across multiple regions and clusters, all while pioneering AI driven observability solutions. If you're enthusiastic about learning at the intersection of observability and AI, and ready to make an impact, we'd love to hear from you!\n\nWe offer a paid 12-week internship, starting in Summer 2026.\n\nAbout the team\n\nThe observability team is an integral part of Roku's central Infrastructure Engineering team, which oversees the service mesh hosting architecture and observability platform that lives on that platform. Together, we are tasked with developing and scaling both the Platform (Kubernetes, Istio, Envoy, operators, etc.) and the Observability stack (OSS/CNCF-supported observability projects). Our goal is to facilitate Roku's shift towards a unified, cloud-agnostic infrastructure where all teams benefit from a common framework with out of the box features.\n\nWithin the observability team, we are dedicated to creating a world-class observability platform. We customize and optimize OSS projects to meet our needs and actively contribute to upstream projects, promoting positive changes and engaging with the broader ecosystem.\n\nWhat you'll be doing:\n\nIn this role, you'll take on exciting projects at the cutting edge of AI and observability. Your primary focus will be exploring and then making proof of concepts for AI/LLM capabilities within our observability stack. To give some potential examples:\n• Discovering and evaluating MCP servers that can be globally hosted to improve the usability and intelligence of our observability platform\n• Developing AI- driven anomaly detection systems to proactively identify issues and patterns in our telemetry data\n• Creating intelligent automation for common observability workflows using LLMs\n• Building proof-of-concepts for AI-assisted troubleshooting and root cause analysis\n• Explore any other options that benefit our platform\n\nAlongside these AI-focused initiatives, you'll work on smaller tasks to gain hands-on experience with our observability stack, collaborating with a passionate team to solve real-world challenges. Your contributions will directly enhance how Roku monitors, analyzes, and optimizes its systems through the power of AI, giving you a chance to learn, innovate, and make an impact at the forefront of observability technology.\n\nWe’re excited if you have:\n• Currently enrolled in a degree program in Computer Science/Engineering or related field and due to graduate in Dec 2026 or later.\n• A strong curiosity and eagerness to learn about observability, cloud platforms, and large-scale systems.\n• Some prior experience with AI and LLM’s in general\n• Some familiarity with concepts around Kubernetes or container orchestration, and an interest in learning how to deploy and manage services in these environments.\n• An understanding of, or experience with, basic DevOps or CI/CD wor\nBenefits\n• Paid Time Off\n• Training Budget\n• Education Support\nResponsibilities\n\nContribute to building the next generation of Roku's AI-enhanced observability platform. Learn about the CNCF open-source ecosystem, including tools for metrics, logs, and tracing. Explore how AI and Large Language Models can revolutionize observability workflows. Problem-solve, work collaboratively with other teams, and explore innovative ways to improve their observability experience through intelligent automation. Grow skills while helping manage large-scale operations involving high-volume data and requests across multiple regions and clusters, all while pioneering AI driven observability solutions.\nKey Aspects\n\nAI-enhanced observability platform, CNCF open-source ecosystem, AI and Large Language Models, observability workflows, intelligent automation, large-scale operations, multi-region clusters.\n\nApply for this Software Engineer Intern, Observability in Cambridge role today via Placed.",
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  "employer_website": "https://www.roku.com",
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  "job_employment_type": "Full–time",
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  "job_posted_at_timestamp": 1773100800,
  "job_posted_at_datetime_utc": "2026-03-10T00:00:00.000Z"
}