GCP Architect – GenAI

Job Title: GCP Architect – GenAI & Enterprise AI Platforms

Location: Dallas, TX (Hybrid)

GCP Architect – GenAI & Enterprise Data Platforms

Job Summary

We are looking for a highly experienced GCP Architect to design and architect enterprise-scale GenAI and RAG-based remediation platforms on Google Cloud. The ideal candidate will define end-to-end cloud architecture, establish BigQuery as the enterprise data foundation, and architect secure, scalable AI workflows integrating legacy systems, modern data platforms, and healthcare-compliant governance frameworks.

This role requires deep expertise in enterprise architecture, AI platform strategy, MLOps, and cloud-native modernization.

Key Responsibilities

Architect end-to-end GenAI remediation platforms leveraging Vertex AI, BigQuery, and GCP-native services.Define enterprise data architecture and establish BigQuery as the centralized source of truth.Design scalable ingestion and normalization frameworks for Mainframe (z/OS), AS400, Splunk, and distributed enterprise systems.Architect RAG pipelines using embedding models, vector search, and BigQuery Vector Search capabilities.Design Human-in-the-Loop (HITL) frameworks integrating analyst feedback into AI model retraining pipelines.Define secure healthcare-compliant AI architectures with row-level security, data masking, encryption, and governance controls.Lead MLOps strategy including model lifecycle management, evaluation, observability, retraining triggers, and performance monitoring.Create reusable cloud architecture standards, deployment patterns, and Terraform-based automation frameworks.Provide architectural leadership across engineering, AI, infrastructure, security, and business teams.Present technical roadmaps, architecture decisions, and AI trade-offs to executive leadership and stakeholders.Required Skills

12+ years of enterprise architecture and cloud engineering experience.Expert-level knowledge of GCP services including:Vertex AIBigQueryDataflowPub/SubCloud RunCloud FunctionsDeep expertise in GenAI, RAG architectures, embeddings, vector databases, and LLM integration.Strong experience designing enterprise-scale data platforms and modernization programs.Experience integrating legacy Mainframe (z/OS), AS400, and enterprise operational systems into cloud ecosystems.Strong expertise in Python, SQL, PySpark, and Terraform.Experience implementing MLOps and AI governance frameworks.Strong leadership, communication, and stakeholder engagement capabilities.