Systems Development Engineer

About the Role

Join the Fire TV System Software Development and Deployment (S2D2) Launch TPM team to build and scale the infrastructure powering millions of devices worldwide. You'll design automation, improve reliability, and leverage AI/ML to enhance our systems, from device software delivery pipelines to cloud services that enable the Fire TV experience.

Key Job Responsibilities

• Design and implement CI/CD pipelines for Fire TV software builds, testing, and OTA delivery.
• Build infrastructure automation for device labs, test farms, and deployment systems.
• Develop AI/ML-powered solutions for anomaly detection, predictive alerting, and automated remediation.
• Create and maintain observability platforms for device metrics, crash analytics, and service health.
• Automate operational workflows using LLMs and agentic AI tools to reduce toil.
• Troubleshoot complex issues spanning device firmware, Android/Fire OS, Vega OS, and cloud services.
• Drive incident response, root cause analysis, and reliability improvements.
• Collaborate with embedded, Android, Vega, and backend teams to improve system performance.

Basic Qualifications

• Experience in automating, deploying, and supporting large-scale infrastructure.
• Experience programming with at least one modern language such as Python, Ruby, Golang, Java, C++, C#, Rust.
• Experience with Linux/Unix.
• Experience with CI/CD pipelines build processes.
• Knowledge of systems engineering fundamentals (networking, storage, operating systems).

Preferred Qualifications

• Experience with distributed systems at scale.
• Experience with AI/ML operations—model deployment, inference pipelines, or MLOps.
• Hands-on experience with LLMs, prompt engineering, or agentic AI workflows.
• Knowledge of embedded systems, device firmware, or OTA update mechanisms.
• Experience with device lab automation (ADB, device farms, hardware-in-the-loop testing).
• Familiarity with crash analytics, log aggregation, and anomaly detection systems.
• Experience building AI-assisted tooling for developer productivity or operations.
• Understanding of video streaming, media pipelines, or smart TV ecosystems.
• AI & Automation Focus: Apply generative AI to automate runbooks, incident triage, and documentation. Build intelligent alerting systems that reduce noise and surface actionable insights. Develop AI-powered code review, test generation, or debugging assistants. Create self-healing infrastructure that detects and remediates issues autonomously.
• Leadership Principles We Value: Dive Deep, Invent and Simplify, Bias for Action, Ownership, Learn and Be Curious.

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