AI Operations Specialist – Customer Support

Sinch

. Map intuitive self-service conversation paths and resolution flows across messaging channels and web support .

Posted 11/8/2026full-timeRemote • PhilippinesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in structuring multi-turn dialogue trees and conversational UI flows, with a strong command of prompt engineering techniques and a deep understanding of support operational metrics. Proficient in integrating conversational AI agents with ticketing platforms and utilizing empirical data for continuous performance benchmarking.

Highest-signal resume keywords

Prompt Engineering TechniquesConversational AI PlatformsSupport Operational MetricsMulti-Turn Dialogue StructuresAPIs and Webhooks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Multi-Turn Dialogue TreesPrompt EngineeringConversational UI FlowsEmpirical Data AnalysisScripting (Python, JavaScript)RAG FrameworksSynthetic Test SuitesConversation AnalyticsBenchmarkingDynamic Context Parameters

Soft Skills

CollaborationEmpathyProblem-Solving

Tools & Technologies

Sinch ChatlayerGoogle DialogflowCognigyZendeskJira Service Desk

Industry Keywords

CPaaSTelecommunicationsCloud SoftwareHigh-Volume Customer Service Operations

Tech Stack

Tools & technologies

CloudJavaScriptPython

About the role

Key responsibilities & impact

Map intuitive self-service conversation paths and resolution flows across messaging channels and web support
Define and maintain agent personas, tone of voice, empathy guidelines, and brand-aligned dialogue
Architect conversational logic for ambiguous intents, edge cases, and graceful failure handling
Formulate, refine, and maintain system prompts, few-shot examples, and dynamic context parameters
Work with knowledge bases and RAG frameworks to ground AI answers in verified documentation
Implement boundary rules, safety filters, and anti-hallucination guardrails
Build and run synthetic test suites, benchmark datasets, and regression checks
Review conversation logs, agent handoffs, and customer drop-offs to identify failure patterns
Drive A/B testing on prompt variants, conversational hooks, and journey branches using CSAT, FCR, and containment metrics
Collaborate with Support Engineering and IT to integrate conversational AI agents with ticketing platforms, CRM systems, and internal APIs
Partner with support managers and product teams to translate product updates and user pain points into automated workflows

Requirements

What you’ll need

Demonstrable experience structuring multi-turn dialogue trees, conversational UI flows, and tailored bot personas in an enterprise or SaaS setting
Strong command of prompt engineering techniques, LLM behavior, context windows, and strategies to minimize hallucination while maximizing resolution accuracy
Proven track record of using empirical data, conversation analytics, and structured evaluation rubrics to continuously benchmark and iterate on AI performance
Deep understanding of support operational metrics (CSAT, deflection/containment rates, Average Handle Time, escalation quality)
Hands-on experience with conversational AI platforms (e.g., Sinch Chatlayer, Google Dialogflow, Cognigy) or modern generative AI agent builders
Familiarity with customer service ticketing systems (Zendesk, Jira Service Desk) and knowledge base management
Basic understanding of APIs, webhooks, and JSON data structures
Experience working in CPaaS, telecommunications, cloud software, or high-volume customer service operations
Hands-on experience evaluating RAG architectures and embedding-based search retrieval systems
Basic scripting skills (Python, JavaScript) for generating synthetic evaluation datasets or testing API endpoints