Lead Data & AI Architect – GCP

Lead Data & AI Architect – GCP Location: Charlotte, United States Work Model: Client-facing; minimum 3 days per week onsite Required Skills & Experience 12+ years of experience in Data, AI, Cloud or Enterprise Architecture, with significant experience leading large-scale technology transformation programs. Extensive experience designing and implementing enterprise-scale solutions on GCP. Deep expertise in GCP data and AI services, including BigQuery, Cloud Storage, Dataflow/Apache Beam, Pub/Sub, Dataproc and Vertex AI. Strong experience designing modern enterprise data platforms and architectures, including data lakes/lakehouses, data warehouses, data products and streaming platforms. Proven experience designing both batch and real-time/streaming data architectures. Strong experience with AI/ML architecture and practical experience with Generative AI and/or agentic AI architectures. Strong understanding of RAG, vector search, embeddings, knowledge architectures, AI orchestration and integration of AI agents with enterprise systems and data. Experience designing secure, governed and production-grade AI platforms. Strong understanding of data security, governance, privacy, lineage and data quality. Proven experience working within financial services, banking or other highly regulated industries. Experience leading architecture discovery, assessment and transformation engagements. Demonstrated ability to translate business requirements and current-state findings into target-state architecture and implementation roadmaps. Strong understanding of cloud scalability, resilience, performance, observability and cost optimization. Experience with DevOps/MLOps and productionization of Data and AI solutions. Excellent executive communication, stakeholder management and influencing skills. Proven ability to lead and mentor multidisciplinary architecture and engineering teams. Preferred Qualifications Google Cloud Professional Cloud Architect and/or Professional Data Engineer certification. Experience with production-scale agentic AI platforms and enterprise AI implementations. Experience with Vertex AI and Google Cloud generative AI capabilities. Experience with enterprise data governance, metadata, catalog and lineage platforms. Experience with Infrastructure as Code, CI/CD and modern cloud engineering practices. Experience defining enterprise architecture standards and technology reference architectures. Experience working directly with C-suite and senior technology leadership in complex transformation programs.