Artificial Intelligence Specialist

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