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You are a Senior Support Engineer who delivers world-class post-deployment support for product and solution deployments. You are highly customer-oriented, calm under pressure, and excellent at triaging complex issues, reproducing problems, and driving cross-functional resolution with Implementation and Engineering teams. You act as the customer’s advocate while ensuring issues are tracked, prioritized, and resolved with clarity, urgency, and high quality.
Job Responsibility:
Own customer-facing incident management and escalations for post-deployment enterprise accounts
Triage incoming issues by gathering context, logs, steps-to-reproduce, and customer impact
Create clear, actionable bug reports and support tickets with detailed reproduction steps and diagnostics
Coordinate closely with Implementation and Engineering teams to drive timely issue resolution
Track and manage SLAs and key support metrics including FRT, TAT, AHT, and CSAT
Provide proactive, regular status updates to customers and internal stakeholders
Communicate effectively with both technical and non-technical customer teams during incidents and escalations
Identify recurring issues and contribute to improvements in documentation, runbooks, and support processes
Maintain and enhance internal knowledge bases, troubleshooting guides, and escalation playbooks
Validate fixes, coordinate customer confirmation, and support post-resolution follow-ups
Participate in escalation and on-call rotations as required
Requirements:
4+ years of experience in Support Engineering, Software Engineering, or Technical Customer Support
Hands-on experience supporting AI/LLM-based applications in production environments
Experience configuring, deploying, or supporting AI agents, workflows, or ML systems
Exposure to prompt engineering and iterative improvement of LLM outputs
Experience running UATs or customer-facing evaluations for AI systems
Proven ability to manage complex enterprise customer issues independently
Familiarity with support metrics such as FRT, AHT, TAT, CSAT
Strong production troubleshooting skills, including diagnosing AI performance and recommending improvements to accuracy and business KPIs