Systems Development Engineer, FireTV S2D2 LTPM Team
Amazon - Bengaluru, Karnataka, IND
Posted Apr 29, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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Schedule
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- Weekend work
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Application
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- Deadline
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Where they hire
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About this role
Systems Development Engineer, FireTV S2D2 LTPM Team Bengaluru, Karnataka, IND About the Role Join the Fire TV System Software Developement 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 - Preferred Qualifications - * Experience with AI/ML operations-model deployment, inference pipelines, or MLOps - * Hands-on experience with LLMs, prompt engineering, or
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