ADCI
Technology
SystemsDevelopmentEngineer,FireTVS2D2LTPMTeam
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Systems Development Engineer, FireTV S2D2 LTPM Team at ADCI. Skills: Systems Development, Infrastructure Automation, AI/ML, DevOps. Design CI/CD pipelines. Implement CI/CD pipelines”
Industry & Context.
Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
Automating, deploying, and supporting large-scale infrastructure, Programming with Python, Ruby, Golang, Java, C++, C#, or Rust, Linux/Unix experience, CI/CD pipelines build processes experience, Systems engineering fundamentals knowledge
Nice to Have
Distributed systems at scale experience, AI/ML operations experience, LLMs, prompt engineering, or agentic AI workflows experience, Embedded systems, device firmware, or OTA update mechanisms knowledge, Device lab automation experience, Crash analytics, log aggregation, and anomaly detection systems familiarity, AI-assisted tooling building experience, Video streaming, media pipelines, or smart TV ecosystems understanding
What You'll Do.
Design CI/CD pipelines
Implement CI/CD pipelines
Build infrastructure automation
Develop AI/ML-powered solutions
Create observability platforms
Maintain observability platforms
Automate operational workflows
Troubleshoot complex issues
Drive incident response
Perform root cause analysis
How You'll Work.
Team & Collaboration
Embedded teams; Android teams; Vega teams; Backend teams
Full Job Description
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 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 d
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