Project Manager

Virtusa; Minneapolis (MN); On-site; USD 120,000 - 160,000; Full time

Job summary

Virtusa Minneapolis is seeking an experienced Conversational AI configuration specialist to deploy and optimize Google CCAI, AWS voice and chat applications, and connect them to customer RAG stores. You will tune grounding and retrieval settings, ensure channel integrations are correct, and document configurations for repeatability.

The role requires hands-on expertise with Dialogflow CX, AWS stacks, and strong debugging skills across consoles, logs, and APIs.

Qualifications

• 5+ years implementing or configuring conversational AI / contact-center platforms.
• Hands-on experience with Google Dialogflow CX and/or Contact Center
• Hands-on experience with at least one AWS conversational stack
• Ability to configure flows, intents/entities or equivalent, knowledge sources, and channel integrations
• Strong debugging skills across console UIs, logs, and webhook/API integrations.

Responsibilities

• Configure Google CCAI components: Dialogflow CX agents/flows, Agent Assist, conversation profiles, and knowledge bases.
• Configure and deploy the AWS voice application
• Configure and deploy the AWS chat application
• Connect deployed applications to the customer RAG / knowledge store
• Tune grounding / retrieval settings in the product consoles so answers use the indexed corpus.
• Apply customer-specific configuration packages; version and document what was deployed.
• Run functional smoke tests across voice, chat, and CCAI experiences after each deployment, including knowledge-grounded questions.
• Troubleshoot configuration and integration defects during go-live; escalate true product defects to the development organization.
• Partner with the Conversational Data Engineer so synthetic conversations and RAG corpora load correctly into each platform.
• Maintain configuration-as-code or structured configuration packages for repeatability.

Skills

Conversational AI

Dialogflow CX

AWS conversational stack

Troubleshooting

Configuration as code

Tools

Dialogflow CX

AWS Connect/Lex

Vertex AI

Job description

Role summary

Configure and deploy the pre-built conversational applications for each customer across three channels: Google
Contact Center AI on GCP, plus voice and chat applications on AWS. You wire each application to the customer
knowledge / RAG store prepared by the Conversational Data Engineer. You specialize in platform configuration,
channel setup, and go-live smoke testing

What success looks like

• CCAI, voice, and chat packages are correctly configured for each customer and demonstrably working

before handoff.

Customer-specific settings are
applied consistently and documented.

Key responsibilities

• Configure Google CCAI components: Dialogflow CX agents/flows, Agent Assist, conversation profiles, and

knowledge bases.

• Configure and deploy the AWS voice application
• Configure and deploy the AWS chat application
• Connect deployed applications to the customer RAG / knowledge store
• Tune grounding / retrieval settings in the product consoles so answers use the indexed corpus.
• Apply customer-specific configuration packages; version and document what was deployed.
• Run functional smoke tests across voice, chat, and CCAI experiences after each deployment, including

knowledge-grounded questions.

• Troubleshoot configuration and integration defects during go-live; escalate true product defects to the

development organization.

• Partner with the Conversational Data Engineer so synthetic conversations and RAG corpora load

correctly into each platform.

• Maintain configuration-as-code or structured configuration packages for repeatability.

Required Qualifications

• 5+ years implementing or configuring conversational AI / contact-center platforms.
• Hands-on experience with Google Dialogflow CX and/or Contact Center
• Hands-on experience with at least one AWS conversational stack
• Ability to configure flows, intents/entities or equivalent, knowledge sources, and channel integrations

without writing the core application.

• Strong debugging skills across console UIs, logs, and webhook/API integrations.

Preferred Qualifications

• Both GCP CCAI and AWS Connect/Lex experience in the same career
• Experience connecting conversational products to Vertex AI Search, Bedrock Knowledge Bases, or

similar RAG services.

• Experience loading training or evaluation conversation sets and knowledge articles.