GCP Gen AI Architect

Location: Irving, TX or Jacksonville, FL (Onsite) – Contract

Responsibilities

• Lead the overall Generative AI, Agentic AI, and data architecture strategy for enterprise-scale banking transformation programs.
• Architect and implement GenAI solutions using LLMs, RAG, Knowledge Graphs, AI Agents, and multi-agent architectures.
• Design scalable AI platforms leveraging GCP services including Vertex AI, Gemini, BigQuery, Dataflow, Pub/Sub, Cloud Run, GKE, Cloud Functions, and Cloud Storage.
• Develop and integrate Customer Data Platform (CDP) architectures supporting Customer 360, identity resolution, master data management, personalization, and real-time customer intelligence.
• Implement RAG architectures, vector databases, embeddings, semantic search, and knowledge retrieval using technologies such as Pinecone, Vertex AI Vector Search, Weaviate, and FAISS.
• Design and implement Agentic AI solutions using frameworks such as LangChain, LangGraph, LlamaIndex, and Semantic Kernel, including prompt engineering and optimization.
• Apply LLM fine-tuning techniques including LoRA and QLoRA across models such as GPT, Gemini, Claude, Llama, and other open-source models.
• Establish secure and compliant AI architectures incorporating AI guardrails, Responsible AI, explainability, privacy, hallucination reduction, IAM, and regulatory controls.
• Define and implement MLOps, LLMOps, observability, monitoring, model governance, and AI lifecycle management frameworks for production AI platforms.
• Lead architecture reviews, solution design workshops, technical governance, and development of reusable AI architecture patterns, frameworks, and best practices.
• Collaborate with Product, Data Engineering, Risk, Fraud, Compliance, and business teams to deliver AI solutions across banking operations, fraud management, financial crimes, customer servicing, and risk & controls.
• Provide technical leadership and mentoring to architects and engineering teams while leveraging Python, SQL, distributed data processing, feature engineering, data lakes, data mesh, and enterprise cloud architecture to drive AI transformation.