Google Cloud Platform Gen AI Architect

Role - Google Cloud Platform Gen AI Architect

Location: Irving/ Jacksonville

Experience: 15+ Years

Domain: Banking, Fraud, Risk & Controls

Position Summary

We are seeking a highly experienced Generative AI Architect to lead the architecture, design, and implementation of next-generation AI solutions. The ideal candidate should possess deep expertise in Generative AI, Agentic AI, Google Cloud Platform Cloud Architecture, Customer Data Platforms (CDP), and enterprise-scale banking solutions, with a proven track record of delivering AI-driven transformation programs.

The role requires close collaboration with business stakeholders, product teams, data architects, risk teams, and engineering leadership to build scalable, secure, and compliant AI solutions leveraging Google Cloud's AI ecosystem.

Key Responsibilities

• Define and drive the overall AI and data architecture strategy for the OMAI program.
• Architect enterprise-scale GenAI solutions leveraging LLMs, Agentic AI, RAG, Knowledge Graphs, and AI Agents.
• Design and implement Customer Data Platform (CDP) integrations to enable unified customer intelligence and personalized AI experiences.
• Build scalable AI platforms using Google Cloud AI and ML services.
• Lead architecture reviews, solution design workshops, and technical governance.
• Design secure AI architectures compliant with banking, risk, regulatory, and data privacy requirements.
• Partner with Product Owners, Data Engineering, Risk, Fraud, and Compliance teams to deliver business outcomes.
• Establish AI MLOps, LLMOps, observability, monitoring, and responsible AI frameworks.
• Drive AI adoption through reusable architecture patterns, frameworks, and best practices.
• Provide technical leadership and mentoring to architects and engineering teams.

Required Skills

• The required skills encompass a strong foundation in Generative AI and Agentic AI, featuring expertise in LLMs (GPT, Gemini, Claude, Llama, and open-source models), RAG architecture, vector databases, embeddings, semantic search, and multi-agent frameworks. This includes proficiency in prompt engineering, fine-tuning approaches like LoRA and QLoRA, AI guardrails, responsible AI, hallucination reduction, and orchestration tools such as LangChain, LangGraph, LlamaIndex, and Semantic Kernel.
• Cloud expertise centers on Google Cloud Platform Architecture, leveraging Vertex AI, Gemini Models, Document AI, BigQuery, Dataflow, Pub/Sub, Cloud Run, GKE, Cloud Functions, Cloud Storage, Dataproc, alongside robust IAM and Security Architecture.
• In the realm of Customer Data Platforms (CDP), the skill set covers enterprise CDP architecture, Customer 360 data modeling, identity resolution, master data management, real-time customer insights, personalization, data governance, privacy controls, and ecosystem integrations.
• Technical capabilities extend to Data & AI Engineering utilizing Python, SQL, distributed data processing, feature engineering, vector databases (Pinecone, Vertex AI Vector Search, Weaviate, FAISS), knowledge graphs, data lakes, and data mesh concepts.
• Finally, the profile requires deep Banking Domain Expertise spanning banking operations, fraud management, risk and controls, regulatory compliance, customer servicing, operational excellence programs, and financial crimes or fraud analytics.