GCP Gen AI Architect

Programmers.io; Irving (TX); On-site; USD 150,000 - 230,000; Full time

Job summary

Programmers.io seeks a highly experienced Generative AI Architect to lead architecture, design, and implementation of next-gen AI solutions. You will architect GenAI and Agentic AI systems on Google Cloud, with a focus on CDP integrations and enterprise banking compliance.

You will collaborate with stakeholders across product, risk, and engineering to deliver scalable AI platforms. You will establish AI MLOps, LLMOps, observability, governance, and secure architectures.

Qualifications

• 15+ years of experience in AI architectures and enterprise systems.
• Proven track record in GenAI, MLOps, and large-scale banking solutions.
• Strong collaboration with business, product, risk, and engineering leaders.

Responsibilities

• Define and drive AI and data architecture strategy for the program.
• Architect GenAI solutions using LLMs, Agentic AI, RAG, and CDP integrations.
• Build secure, compliant, scalable AI platforms on Google Cloud.
• Lead architecture reviews, governance, and technical workshops.
• Mentor architects and engineering teams.

Skills

Generative AI

Agentic AI

LLMs

RAG architecture

Prompt engineering

LoRA/QLoRA

Responsible AI

LangChain

Document AI

BigQuery

Dataflow

Pub/Sub

GKE

Cloud Functions

IAM & Security

CDP

Customer 360

Identity Resolution

Python

SQL

Distributed Data Processing

Tools

GCP Cloud Platform

BigQuery

Dataflow

Pub/Sub

GKE

Cloud Functions

IAM

Job description

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

Hire Type: Full Time / Contract

Experience: 15+ Years

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.

Document AI

BigQuery

Dataflow

Pub/Sub

GKE

Cloud Functions

IAM and Security Architecture

Customer Data Platform (CDP)

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.

Python

SQL

Distributed Data Processing