Voice AI Lead Architect Data Architecture - Banking
Job Description
Role SummaryWe 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 ResponsibilitiesAct 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 / CCAIVertex 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 enablementBuild 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 SkillsStrong expertise in Voice AI / Conversational AI architectureDeep 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 frameworksStrong stakeholder engagement and consulting skillsExperience1218+ years in architecture with focus on data + AI platformsProven experience in Voice AI / IVR / Contact Center transformation programsHands-on experience designing enterprise data platforms in bankingExperience working in regulated financial environmentsTrack record of driving data-driven CX transformation initiativesPreferred QualificationsExperience with Customer 360, real-time personalization, and behavioral analyticsExposure to multi-agent AI architectures and tool invocation frameworksExperience with CCaaS platforms (Google CES/CXAS, Genesys, NICE, Amazon Connect)Strong understanding of AI/ML lifecycle, MLOps, and data governanceExperience working with Tier-1 banks or large financial institutionsCertificationsGoogle Cloud Professional Data Engineer (Highly Preferred)Google Professional Cloud ArchitectGoogle Machine Learning EngineerCertifications in Conversational AI (Dialogflow CX or equivalent)TOGAF / Enterprise Architecture certificationsData certifications (good to have): CDMP, Databricks, SnowflakeTPBN1_UKTJ