Engineer II, Systems Reliability Engineering

As an Engineer II, Systems Reliability Engineering, you will provide technical leadership for Product Creation and Master Data operations across FlexPLM, DaVinci, Infor Nexus, MDM services, and related integrations. This role, based in GCC Mexico, reports directly to the Manager, Systems Reliability Engineering, LATAM, who reports to Simon Aguilera. As an individual contributor and technical lead, you will guide engineers, coordinate complex investigations and improve reliability through consistent ways of working, automation and Agentic AI. The ML08 manager retains people-management accountability.

• Lead complex production investigations across applications, APIs, middleware, queues, batch processes and file feeds; coordinate incident resolution, root cause analysis and corrective actions.
• Translate service-level objectives into actionable monitoring, queue-age and data-integrity checks; identify capacity constraints and recommend priorities to the regional manager.
• Provide technical mentoring, peer review and knowledge sharing for Engineer I colleagues; coordinate technical work and raise staffing or performance concerns to the ML08 manager.
• Maintain runbooks, dependency maps and operational playbooks; lead knowledge transfer, release validation and recovery exercises using disciplined incident, problem and change practices.
• Build and improve approved Agentic AI workflows for triage, investigation and runbook assistance; evaluate outputs, enforce approval boundaries and retain evidence of operational actions.
• Coordinate clear handovers across India and LATAM and collaborate with product, engineering, infrastructure, enterprise data and business teams on recurring reliability improvements.

• 5+ years of experience in IT production support, application operations, platform engineering or Site Reliability Engineering, including technical leadership of enterprise services.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
• Experience supporting PLM, MDM, enterprise data, integration platforms or comparable business-critical applications, with the ability to learn the portfolio’s application-specific processes.
• Strong understanding of APIs, middleware, queues, batch processing, file feeds, data controls and upstream and downstream dependencies.
• Practical experience with ITSM, root cause analysis, technical mentoring, automation and approved AI tools; ability to validate Agentic AI outputs and apply human oversight.