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Tier-1 employer and broad observability/AI/platform skillset create moderate candidate competition.
Platform SRE and observability skills transfer across industries but require enterprise tooling experience.
Explicit 8–10 years plus numerous mandatory platform, observability, and AI technology requirements.
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Own deployment, configuration, and continuous management of Life Cycle Management system using Splunk to monitor non-production R&D resources across engineering labs.
Design and optimize dashboards integrating diverse data feeds; utilize AI to analyze alerting data delivering actionable insights.
Collaborate with cross-functional teams to align observability solutions with business objectives, document processes, and participate in global planning to enhance lab infrastructure reliability and efficiency.
Bachelor’s degree in Computer Science, Electronics & Communications Engineering, Information Technology, or related technical discipline.
8–10 years professional experience in enterprise software engineering, SRE, Platform Engineering, DevOps, or related technical leadership roles.
Strong skills in Java, Spring Framework, REST APIs, Kubernetes, Docker, Linux/Unix, CI/CD, cloud-native deployment, and hands-on AI technologies such as LangGraph and LangChain.
Experience with Oracle databases, SQL optimization, PL/SQL, ETL frameworks, monitoring solutions design, DevOps tools (Git, Jenkins, Maven, Jira), and proven troubleshooting and root cause analysis capabilities.
Experienced technical leader capable of driving observability and AI-enabled monitoring in large-scale, globally distributed R&D engineering environments.
Strong background in combining enterprise software engineering and AI frameworks to improve lifecycle management and operational insights.
Demonstrated ability to lead cross-functional initiatives, integrate heterogeneous data sources, and produce measurable impact on system uptime, cost savings, and actionable intelligence.