Posted 01 June, 2026
Contact Center AI (Gemini Enterprise for CX) - Engineer
NR Consulting - India
Remote, IN
Full Time
Reference: 26-05631-2220-1
Title: Contact Center AI (Gemini Enterprise for CX) - Engineer
Location: Remote
Exp: 5+ years
Job Description:
Required Qualifications:
• Experience: 5+ years of experience in AI/ML or software engineering, with a significant focus on conversational AI and contact center solutions.
• Google Cloud Platform (GCP) Expertise: Proven, hands-on experience with Vertex AI (generative AI features, custom model deployment, Vertex AI Search, Vector Search).
• Conversational AI Engineering: Deep hands-on experience with CX Agent Studio / Dialogflow CX (agent design, fulfillment, versioning, environments).
• Core Product Surface Knowledge: Hands-on experience with Agent Assist (knowledge connectors, summarisation, smart reply) and CX Insights (topic modelling, sentiment analysis, QA scorecards).
• Data Pipelines: Experience using BigQuery for data pipelines, analytics, and ML integration.
• Advanced AI Architectures: Deep expertise in Gemini model integration, prompt engineering, and RAG architecture design.
• LLM Production Deployment: Hands-on experience deploying and integrating third-party LLMs in production environments.
• Contact Center Domains: Strong understanding of contact center operations, technologies, CCaaS platforms (UJET, CCAIP, Genesys), and telephony/chat integration patterns.
• Programming & API Design: Strong programming proficiency in Python, along with experience in API design (RESTful, gRPC) and webhook integrations.
• Communication: Excellent communication and presentation skills, with the ability to articulate technical concepts to both engineers and C-level stakeholders.
Useful Qualifications:
• Familiarity with Agile development methodologies.
• Industry certifications in relevant technologies.
• Experience tuning applications for non-functional requirements (usability, maintainability, scalability, availability, security, portability, etc.).
• Exposure to relational and NoSQL datastores.
• Familiarity with frontend web technologies, particularly React or Angular.
• Experience using multi-cloud offerings and solutions (Google Cloud Platform, Microsoft Azure, or Amazon AWS).
Scope of Work Delivery Expectations:
Below covers the scope of work we anticipate the contractor supporting throughout the project timeline.
Scope and Solution Expectations:
• Architecture & Technical Design: Lead the technical design of complex GECx solutions, defining architectures for agent creation, orchestration, supervision, and self-optimisation loops. Design multi-agent systems using Google Agent Development Kit (ADK), LangGraph, and LangChain across Commerce Agents, Agent Assist, and CX Insights.
• CX Agent Studio Deployments: Architect and build advanced conversational agents within CX Agent Studio (Dialogflow CX), blending deterministic conversation flows with generative AI capabilities, complex dialogue flows, webhook integrations, and generative fallback handlers.
• Model Deployment & RAG Pipelines: Deploy and fine-tune Gemini models on Vertex AI for domain-specific tasks (intent detection, entity extraction, response generation, summarisation). Develop RAG architectures using Vertex AI Vector Search and build embedding pipelines for unstructured data ingestion (chunking, vector embedding generation, metadata management).
• Multi-Modal & Product Integration: Integrate Gemini and third-party LLMs into Commerce Agents and CX Agent Studio for multimodal inputs (audio, images, video). Implement prompt engineering, chain-of-thought reasoning, and tool-use patterns within workflows.
• CCaaS & Platform Integration: Implement Agent Assist features (generative knowledge assist, smart reply, summarisation, live translation) integrated with CCaaS platforms like UJET/CCAIP. Integrate GECx solutions with CCaaS platforms (UJET, CCAIP, Genesys, etc.) using robust API layers for real-time data exchange.
• Data Analytics & Insights: Define data architectures in BigQuery for conversational data, including training pipelines, inference stores, and Insights analytics layers. Configure and optimise CX Insights pipelines to surface call drivers, sentiment trends, and KPIs.
• Migrations & Lifecycle Management: Lead Dialogflow ES → CX Agent Studio migrations, validating performance post-migration. Manage the full agent lifecycle in production: deployment, A/B experimentation, human supervision workflows, and AI-driven self-optimisation.
• Compliance & Best Practices: Ensure all designs align strictly with Google Cloud best practices for security, scalability, and availability.
Location: Remote
Exp: 5+ years
Job Description:
Required Qualifications:
• Experience: 5+ years of experience in AI/ML or software engineering, with a significant focus on conversational AI and contact center solutions.
• Google Cloud Platform (GCP) Expertise: Proven, hands-on experience with Vertex AI (generative AI features, custom model deployment, Vertex AI Search, Vector Search).
• Conversational AI Engineering: Deep hands-on experience with CX Agent Studio / Dialogflow CX (agent design, fulfillment, versioning, environments).
• Core Product Surface Knowledge: Hands-on experience with Agent Assist (knowledge connectors, summarisation, smart reply) and CX Insights (topic modelling, sentiment analysis, QA scorecards).
• Data Pipelines: Experience using BigQuery for data pipelines, analytics, and ML integration.
• Advanced AI Architectures: Deep expertise in Gemini model integration, prompt engineering, and RAG architecture design.
• LLM Production Deployment: Hands-on experience deploying and integrating third-party LLMs in production environments.
• Contact Center Domains: Strong understanding of contact center operations, technologies, CCaaS platforms (UJET, CCAIP, Genesys), and telephony/chat integration patterns.
• Programming & API Design: Strong programming proficiency in Python, along with experience in API design (RESTful, gRPC) and webhook integrations.
• Communication: Excellent communication and presentation skills, with the ability to articulate technical concepts to both engineers and C-level stakeholders.
Useful Qualifications:
• Familiarity with Agile development methodologies.
• Industry certifications in relevant technologies.
• Experience tuning applications for non-functional requirements (usability, maintainability, scalability, availability, security, portability, etc.).
• Exposure to relational and NoSQL datastores.
• Familiarity with frontend web technologies, particularly React or Angular.
• Experience using multi-cloud offerings and solutions (Google Cloud Platform, Microsoft Azure, or Amazon AWS).
Scope of Work Delivery Expectations:
Below covers the scope of work we anticipate the contractor supporting throughout the project timeline.
Scope and Solution Expectations:
• Architecture & Technical Design: Lead the technical design of complex GECx solutions, defining architectures for agent creation, orchestration, supervision, and self-optimisation loops. Design multi-agent systems using Google Agent Development Kit (ADK), LangGraph, and LangChain across Commerce Agents, Agent Assist, and CX Insights.
• CX Agent Studio Deployments: Architect and build advanced conversational agents within CX Agent Studio (Dialogflow CX), blending deterministic conversation flows with generative AI capabilities, complex dialogue flows, webhook integrations, and generative fallback handlers.
• Model Deployment & RAG Pipelines: Deploy and fine-tune Gemini models on Vertex AI for domain-specific tasks (intent detection, entity extraction, response generation, summarisation). Develop RAG architectures using Vertex AI Vector Search and build embedding pipelines for unstructured data ingestion (chunking, vector embedding generation, metadata management).
• Multi-Modal & Product Integration: Integrate Gemini and third-party LLMs into Commerce Agents and CX Agent Studio for multimodal inputs (audio, images, video). Implement prompt engineering, chain-of-thought reasoning, and tool-use patterns within workflows.
• CCaaS & Platform Integration: Implement Agent Assist features (generative knowledge assist, smart reply, summarisation, live translation) integrated with CCaaS platforms like UJET/CCAIP. Integrate GECx solutions with CCaaS platforms (UJET, CCAIP, Genesys, etc.) using robust API layers for real-time data exchange.
• Data Analytics & Insights: Define data architectures in BigQuery for conversational data, including training pipelines, inference stores, and Insights analytics layers. Configure and optimise CX Insights pipelines to surface call drivers, sentiment trends, and KPIs.
• Migrations & Lifecycle Management: Lead Dialogflow ES → CX Agent Studio migrations, validating performance post-migration. Manage the full agent lifecycle in production: deployment, A/B experimentation, human supervision workflows, and AI-driven self-optimisation.
• Compliance & Best Practices: Ensure all designs align strictly with Google Cloud best practices for security, scalability, and availability.
