GCP Gen AI Architect

Position: GCP Gen AI Architect

Location: Irving, TX / Jacksonville, FL (Onsite)

Hire Type: Full Time / Contract

Experience: 15+ Years

Domain: Banking, Fraud, Risk & Controls

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, GCP 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:

Generative AI & Agentic AI

LLMs including GPT, Gemini, Claude, Llama, and open-source models.

RAG architecture, vector databases, embeddings, semantic search.

Multi-agent and Agentic AI frameworks.

Prompt Engineering and Prompt Optimization.

Fine-tuning approaches such as LoRA and QLoRA.

AI Guardrails, Responsible AI, Explainability, and Hallucination Reduction.

LangChain, LangGraph, LlamaIndex, Semantic Kernel.

GCP Architecture

Vertex AI

Gemini Models

Document AI

BigQuery

Dataflow

Pub/Sub

Cloud Run

GKE

Cloud Functions

Cloud Storage

Dataproc

IAM and Security Architecture

Customer Data Platform (CDP)

Enterprise Customer Data Platform architecture.

Customer 360° data modeling.

Identity Resolution and Master Data Management.

Real-time customer insights and personalization.

Data governance, consent management, and privacy controls.

Integration with marketing, analytics, and AI ecosystems.

Data & AI Engineering

Python

SQL

Distributed Data Processing

Feature Engineering

Vector Databases (Pinecone, Vertex AI Vector Search, Weaviate, FAISS)

Knowledge Graphs

Data Lake and Data Mesh concepts

Banking Domain Expertise

Banking Operations

Fraud Management

Risk & Controls

Regulatory Compliance

Customer Servicing

Operational Excellence Programs

Financial Crimes/Fraud Analytics