AI Operations Specialist – Customer Support

About the Role

Sinch is seeking an AI Operations Specialist to join their global customer support team. This role serves as a bridge between technical infrastructure and human-centric support, focusing on the development, optimization, and maintenance of automated support workflows across messaging channels. You will collaborate with cross-functional teams, including product, engineering, and IT, to architect scalable automated communication solutions. The role involves managing the logic and tone of conversational agents, utilizing data-driven insights to improve system performance, and ensuring AI interactions are helpful, brand-aligned, and effective at handling complex customer inquiries.

Requirements

• Qualified candidates will possess demonstrable experience in structuring multi-turn dialogue trees and conversational UI flows within enterprise or SaaS environments.
• You should have a strong command of prompt engineering techniques, a deep understanding of LLM behaviors, and strategies to minimize hallucinations while maximizing resolution accuracy.
• The role requires proven expertise in using conversation analytics and evaluation rubrics to benchmark and iterate on AI performance, alongside a solid grasp of support operational metrics such as CSAT, containment rates, and average handle time.
• Technical proficiency in conversational AI platforms like Sinch Chatlayer, Google Dialogflow, or Cognigy is essential.
• Furthermore, you should be familiar with ticketing systems like Zendesk or Jira and have a basic understanding of APIs, JSON data structures, and webhooks.
• Hands-on experience evaluating RAG architectures and basic scripting skills in Python or JavaScript to generate synthetic datasets are also highly valued.

Responsibilities

• Your primary responsibilities include mapping intuitive self-service conversation paths and defining agent personas, tone, and empathy guidelines.
• You will be tasked with architecting conversational logic for complex intents and edge cases, while simultaneously formulating and maintaining system prompts and dynamic context parameters.
• A significant portion of your time will involve working with RAG frameworks to ground AI answers in verified documentation and implementing safety filters and guardrails.
• You will build and run synthetic test suites and regression checks to ensure reliability.
• Additionally, you will review conversation logs and customer drop-offs to identify failure patterns, drive A/B testing on prompt variants, and collaborate with IT and product teams to integrate AI agents with CRM systems and ticketing platforms to turn user pain points into automated workflows.