AI Operations Engineering Technical Leader

Meet the Team  Global Lab Solutions (GLS) is a centralized, globally focused team responsible for standardizing best practices, driving innovation, and ensuring operational excellence across Engineering Labs worldwide. Our team is structured around core service offerings such as compliance (ISO-9001/14001, calibration, ESD), system and lab administration, infrastructure monitoring, and tool support. Specialized areas like Engineering Inventory Management, Lab Space Planning, and Lab Information Security are managed by sub-functional experts within the team. The primary objectives of GLS include improving lab efficiency, ensuring compliance and safety, enhancing observability through technologies like Splunk, and supporting scalability and reliability of lab operations via AI-driven insights and data-driven decision-making. Our key stakeholders are engineering teams, lab operations personnel, and leadership across global R&D and innovation hubs. We work closely with internal teams such as IT, Facilities, InfoSec, Procurement, Asset Management, and Engineering leadership to ensure alignment of lab services with business and technical goals.

You will be primarily responsible for the deployment, configuration, and continuous management of Life Cycle Management system that involves Splunk across engineering labs to monitor non-production R&D resources. You will design and optimize dashboards, integrate diverse data feeds, and use AI to analyze alerting data for actionable insights. Day-to-day activities include working with cross-functional teams to align observability solutions with business objectives, documenting monitoring processes, and participating in global discussions and planning. They will also contribute to the implementation of best practices, drive performance improvements, and support the overall reliability and efficiency of lab infrastructure. Success in this role will be measured by: Uptime and reliability of monitoring systems and dashboards Efficient life cycle management measured in terms of quarterly $ savings Number and quality of actionable insights generated through Splunk and AI Timeliness and effectiveness of integrating new data feeds Feedback from internal stakeholders on system usability and value Documentation completeness and adherence to best practices Proactive identification and remediation of vulnerabilities and performance bottlenecks Cross-functional engagement and alignment with organizational goals Meeting or exceeding KPIs related to system observability, user adoption, and operational impact will define performance excellence in this role.

Bachelor’s degree in computer science, Electronics & Communications Engineering, Information Technology, or a related technical discipline. Minimum 8–10 years of professional experience in enterprise software engineering, Site Reliability Engineering (SRE), Platform Engineering, DevOps, or related technical leadership roles. Strong experience designing, developing, and supporting large-scale enterprise applications using Java, Spring Framework, Spring Boot, REST APIs, and modern application architectures. Experience with Kubernetes, Docker, Linux/Unix environments, CI/CD pipelines, and cloud-native deployment models. Hands-on experience with AI technologies including LangGraph, MCP, RAG architectures, Vector Databases, LangChain, Prompt Engineering, or similar AI frameworks. Strong experience with Oracle databases, SQL optimization, PL/SQL, ETL frameworks, and enterprise data integration. Experience designing dashboards, operational metrics, monitoring solutions, and platform observability. Strong knowledge of DevOps tools including Git, Jenkins, Maven, Jira, and CI/CD automation. Demonstrated ability to troubleshoot production issues, perform root cause analysis, and improve system reliability. Excellent verbal and written communication skills with the ability to collaborate effectively across global engineering