Conversational Platform Specialist

Acunor Inc

  • NULL, NJ
  • Today
  • Remote
  • $65–$70

Highlights

The role focuses on configuring Google Contact Center AI (CCAI)/Dialogflow CX and AWS-based voice and chat solutions , integrating them with enterprise knowledge and RAG (Retrieval-Augmented Generation) services, and ensuring that each deployment is properly configured, tested, documented, and ready for production use. About the Role We are looking for an experienced Conversational Platform Specialist to configure, deploy, and support conversational AI applications across Google Cloud Platform (GCP) and AWS .

Numbers & Facts

LocationNULL, NJ (
Remote
)
Salary$65–$70

Description

Conversational Platform Specialist
Location: Remote
Experience: 5+ Years
About the Role
We are looking for an experienced Conversational Platform Specialist to configure, deploy, and support conversational AI applications across Google Cloud Platform (GCP) and AWS.
The role focuses on configuring Google Contact Center AI (CCAI)/Dialogflow CX and AWS-based voice and chat solutions, integrating them with enterprise knowledge and RAG (Retrieval-Augmented Generation) services, and ensuring that each deployment is properly configured, tested, documented, and ready for production use.
This is primarily a platform configuration, integration, and deployment role, rather than a core conversational application development position.
Key Responsibilities
  • Configure and deploy conversational AI applications across GCP and AWS.
  • Configure Google CCAI / Dialogflow CX, including:
    • Agents and flows
    • Intents and entities
    • Agent Assist
    • Conversation profiles
    • Knowledge bases and knowledge sources
  • Configure and deploy AWS-based voice and chat applications using platforms such as Amazon Connect and Amazon Lex.
  • Integrate conversational applications with enterprise RAG and knowledge stores.
  • Configure and tune grounding/retrieval settings to ensure responses use the appropriate indexed knowledge.
  • Apply customer-specific configuration packages and maintain proper versioning and deployment documentation.
  • Configure conversational channels and integrations without requiring development of the underlying core application.
  • Perform functional and go-live smoke testing across voice, chat, and contact-center experiences.
  • Validate knowledge-grounded questions and responses after deployments.
  • Troubleshoot platform configuration, API, webhook, integration, and deployment issues.
  • Work with data and engineering teams to ensure conversational datasets and knowledge corpora are correctly integrated with the platforms.
  • Maintain configuration-as-code or structured configuration packages to support repeatable deployments.
Required Qualifications
  • 5+ years of experience implementing, configuring, or supporting conversational AI or contact-center platforms.
  • Strong hands-on experience with Google Dialogflow CX and/or Google Contact Center AI (CCAI).
  • Hands-on experience with at least one AWS conversational technology stack, preferably Amazon Connect and/or Amazon Lex.
  • Experience configuring conversational agents, flows, intents, entities, knowledge sources, and channel integrations.
  • Experience integrating applications through APIs and webhooks.
  • Strong troubleshooting skills across platform consoles, logs, integrations, and deployment environments.
  • Ability to configure and deploy conversational solutions in enterprise/customer environments.
Preferred Qualifications
  • Hands-on experience with both Google CCAI/Dialogflow CX and AWS Connect/Lex.
  • Experience integrating conversational applications with RAG/knowledge retrieval solutions.
  • Experience with Vertex AI Search, Amazon Bedrock Knowledge Bases, or similar enterprise knowledge platforms.
  • Experience configuring or tuning knowledge-grounded conversational responses.
  • Experience loading training, synthetic, or evaluation conversation datasets.
  • Familiarity with configuration management, version-controlled configuration, and repeatable deployment practices.

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