Technical Support Engineer, AI Cloud Platform

Omilia; United States; À distance; USD 70 000 - 100 000; Plein temps

Avantages offerts par ce poste

Private health insurance

Apple gear

Competitive salary

Long-term employment

Résumé du poste

Omilia in the United States is seeking a Technical Support Engineer for the Omilia Cloud Platform. You will be the first line of defense for enterprise customers, diagnosing issues across speech recognition, NLU, dialogue management and telephony integration, and guiding tickets to resolution.

You’ll reproduce problems in lab environments, participate in incident bridges, document learnings, and provide data-driven feedback to Product and Development.

Qualifications

• 2+ years in a technical support position or a related degree.
• Strong problem-solving skills with a methodical approach and evidence-based reasoning.
• Excellent English, verbal and written communication with non-technical stakeholders.

Responsabilités

• Own the full lifecycle of support requests from triage to resolution.
• Diagnose issues across ASR, NLU, dialogue management and telephony integration.
• Reproduce issues in lab environments before fixes and verify candidate solutions.
• Participate in bridge calls during critical incidents and on-call escalations.
• Document how-to guides and root-cause analyses from resolved cases.
• Provide data-driven feedback to Product and Development to prevent recurrence.

Connaissances

Technical support

Analytical

Communication

Linux

Networking basics

APIs

Jira/Salesforce

Time management

Ownership

Formation

Bachelor’s degree in Computer Science or related field

Outils

AWS

Azure

Docker

Kubernetes

Jira

Salesforce

Description du poste

Omilia in the United States is seeking a Technical Support Engineer for the Omilia Cloud Platform. You will be the first line of defense for enterprise customers, diagnosing issues across speech recognition, NLU, dialogue management and telephony integration, and guiding tickets to resolution.

You’ll reproduce problems in lab environments, participate in incident bridges, document learnings, and provide data-driven feedback to Product and Development.