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Tier-1 employer, metro location, and broad multi-skill requirements increase candidate competition.
Requires specialized SRE/platform, observability and AI tooling experience, making industry transitions difficult.
Explicit 8–10 years plus multiple mandatory technologies and leadership requirements tighten filters.
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Own deployment, configuration, and continuous life cycle management of Splunk-based monitoring systems across engineering labs for non-production resources.
Design and optimize dashboards, integrate diverse data feeds, and leverage AI to analyze alert data into actionable insights that improve lab infrastructure reliability and efficiency.
Collaborate cross-functionally to align observability solutions with business objectives and drive performance improvements while ensuring documentation and best practice adherence.
Bachelor’s degree in Computer Science, Electronics & Communications Engineering, IT, or related technical field.
8–10 years professional experience in enterprise software engineering, SRE, platform engineering, DevOps, or technical leadership roles.
Hands-on expertise in Java, Spring Boot, REST APIs, Kubernetes, Docker, Linux/Unix, CI/CD, Oracle databases, SQL/PLSQL, DevOps tools (Git, Jenkins, Maven, Jira), and AI technologies including LangGraph, MCP, RAG architectures, Vector Databases, or LangChain.
Work Experience Required: Minimum 8–10 years professional experience.
Experienced technical leader comfortable managing globally distributed engineering teams and complex, large-scale enterprise monitoring platforms.
Strong background in software engineering with AI integration and enterprise data platform design focused on observability and actionable analytics.
Proven ability to architect scalable, AI-enabled life cycle management solutions using advanced AI frameworks and operational analytics tools like Splunk.