Role Summary
We are seeking a seasoned Voice AI Lead Architect with strong Data Architecture expertise to lead the design and implementation of next-generation Voice/Agentic AI solutions for a leading banking client on GCP. This role combines conversational AI, data strategy, and customer engagement, acting as a trusted advisor to drive intelligent, data-driven IVR transformation.
Key Responsibilities
* Act as the onsite Voice AI and Data Architecture lead, building strong relationships with banking stakeholders across business, data, and IT teams.
* Design and deliver Voice AI / Agentic IVR solutions leveraging:
* Google CES/CXAS, Dialogflow CX / CCAI
* Vertex AI (LLMs, RAG, agent frameworks)
* Define and implement enterprise data architecture for Voice AI:
* Conversation data pipelines (real-time + batch)
* Integration with data lakes, warehouses (BigQuery)
* Customer 360 and contextual data enablement
* Build RAG-based knowledge systems integrating structured and unstructured banking data.
* Architect data-driven decisioning for voice agents (personalization, next-best action, fraud detection signals).
* Ensure integration with core banking, CRM, and analytics platforms.
* Establish data governance, lineage, quality, and compliance frameworks (GDPR, PCI-DSS).
* Drive conversation analytics, observability, and feedback loops to continuously improve AI performance.
Key Skills
* Strong expertise in Voice AI / Conversational AI architecture
* Deep knowledge of Data Architecture (data lakes, pipelines, streaming, analytics)
* Experience with GCP data stack (BigQuery, Pub/Sub, Dataflow, Cloud Storage)
* Understanding of RAG, embeddings, and knowledge retrieval frameworks
* Strong stakeholder engagement and consulting skills
Experience
* 12–18+ years in architecture with focus on data + AI platforms
* Proven experience in Voice AI / IVR / Contact Center transformation programs
* Hands-on experience designing enterprise data platforms in banking
* Experience working in regulated financial environments
* Track record of driving data-driven CX transformation initiatives
Preferred Qualifications
* Experience with Customer 360, real-time personalization, and behavioral analytics
* Exposure to multi-agent AI architectures and tool invocation frameworks
* Experience with CCaaS platforms (Google CES/CXAS, Genesys, NICE, Amazon Connect)
* Strong understanding of AI/ML lifecycle, MLOps, and data governance
* Experience working with Tier-1 banks or large financial institutions
Certifications
* Google Cloud Professional Data Engineer (Highly Preferred)
* Google Professional Cloud Architect
* Google Machine Learning Engineer
* Certifications in Conversational AI (Dialogflow CX or equivalent)
* TOGAF / Enterprise Architecture certifications
* Data certifications (good to have): CDMP, Databricks, Snowflake