Google CCAI & GECX Pod Lead Development Architect

Location: Charlotte, NC

Duration: 6+ Months

Open Positions: 1

Experience: 8+ Years

Work Authorization: GC, USC, and GC EAD (Last Preference)

We are seeking an experienced Google CCAI / GECX Pod Lead to lead a small team of Conversational AI developers in designing, developing, and delivering enterprise-scale customer experience solutions on the Google Cloud ecosystem.

The ideal candidate should possess strong hands‑on expertise in Google Contact Center AI (CCAI), Dialogflow CX, Google GECX (GenCX) Playbooks, Generative AI, Python integrations, and cloud-native development
, while also demonstrating proven experience leading Agile development pods of 3–10 developers
.

• Lead and mentor a pod of Conversational AI developers, engineers, and integration specialists.
• Provide technical guidance, code reviews, design reviews, and development best practices.
• Allocate tasks, track sprint progress, manage delivery commitments, and remove technical blockers.
• Collaborate with architects, business analysts, product owners, and customer stakeholders.
• Drive engineering excellence through reusable frameworks, coding standards, automation, and Dev Ops best practices.

• Design and implement intelligent voice and chat virtual agents using Google Dialogflow CX and Google Contact Center AI (CCAI).
• Define conversation architecture, intent strategy, entity models, routing structures, fulfillment logic, and conversational experiences.
• Lead development of reusable conversational components and enterprise bot frameworks.
• Ensure scalable, maintainable, and high‑performing customer interaction solutions.

• Lead implementation of Google GECX (GenCX) Playbooks and AI‑powered agent assistance capabilities.
• Design Generative AI‑based customer journeys using Gemini and Vertex AI services.
• Define prompting strategies, grounding mechanisms, response orchestration, and AI governance controls.
• Guide teams on prompt engineering, optimization, tuning, and evaluation.
• Oversee development of Python‑based fulfillment services and webhooks.
• Design integrations with enterprise applications, CRM systems, customer databases, middleware platforms, and third‑party APIs.
• Establish secure integration patterns leveraging OAuth, JWT, REST APIs, gRPC, and cloud‑native services.
• Lead orchestration design for backend workflows, customer authentication, profile retrieval, and transaction services.

• Lead and support:
• Genesys to Google CCAI
• NICE CXone to Google CCAI
• Amazon Connect to Google CCAI
• Legacy IVR Modernization
• Dialogflow ES to Dialogflow CX Migration
• Traditional Chatbot to Generative AI Transformation
• Conduct current‑state assessments and discovery.
• Perform conversation flow analysis and redesign.
• Handle intent and entity mapping.
• Plan and execute migration strategies.
• Develop knowledge migration strategies.
• Support QA, deployment, and production rollout.

• Own pod‑level delivery commitments, sprint planning, estimation, and reporting.
• Monitor development quality, code coverage, defect trends, and operational metrics.
• Manage risks, dependencies, and technical escalations.
• Contribute to solution architecture, effort estimation, and proposal activities.
• Support UAT, go‑live planning, hypercare, and production stabilization.

• Google Contact Center AI (CCAI)
• Dialogflow CX
• Virtual Agent Development
• Conversational AI
• Voicebot & Chatbot Development

• Google GECX / GenCX Playbooks
• Prompt Engineering
• LLM Integration
• AI Agent Development

• Python
• REST API Development
• gRPC
• Webhook Development
• Cloud Functions
• Big Query
• Pub/Sub

• SQL
• Postman
• JIRA
• Agile / Scrum

• Experience leading development pods or Agile teams of 3–10 engineers
  .
• Strong mentoring and coaching skills.
• Experience conducting code reviews, design reviews, and technical governance.
• Ownership of sprint delivery and release management.
• Stakeholder management across business and technology teams.
• Experience coordinating offshore/onshore delivery teams is preferred.

• Experience in telecom, banking, healthcare, retail, or customer service environments.
• Knowledge of RAG (Retrieval Augmented Generation) solutions.
• Experience with Lang Chain, Lang Graph, CrewAI, and Agentic AI frameworks.
• Conversational analytics and speech analytics experience.
• Omnichannel customer engagement platforms.
• Customer experience transformation programs.