Live opening · Posted 4 days ago
At a glance
The key details from the original listing.
Your early-applicant advantage
Live timing from JobBeeper.
About the role
Description supplied by the original job listing.
As Principal / Distinguished Architect for Google Cloud AI, you will spearhead the design, delivery, and governance of next-generation AI and Generative AI solutions leveraging the Google AI stack.
Roles & Responsibilities
AI & Cloud Architecture Leadership
Own end-to-end architecture for AI, GenAI, and data-driven platforms on Google Cloud Platform.
Define enterprise reference architectures, blueprints, and guardrails aligned with Google Cloud best practices.
Lead critical architecture decisions for large-scale, mission-critical AI platforms across multiple customer programs.
Generative AI, Gemini & Agentspace
Architect and govern GenAI solutions using Vertex AI (Gemini models, Model Garden, Extensions), Google Agentspace, and Vertex AI Search & Conversation.
Design advanced GenAI patterns including Retrieval-Augmented Generation (RAG), agentic workflows, multi-agent orchestration, and enterprise system integration.
Define Responsible AI, safety, and governance frameworks aligned to Google AI principles.
Google AI & Data Platform Architecture
Lead scalable AI and data platform architectures utilizing BigQuery, BigLake, Cloud Storage, Dataflow, Dataproc, Pub/Sub, AlloyDB, Spanner.
Architect secure, multi-project GCP environments with strong network isolation and identity controls.
Ensure high availability, resiliency, and performance for AI workloads.
MLOps, LLMOps & Engineering Excellence
Define and enforce MLOps / LLMOps standards on GCP, including Vertex AI Pipelines, CI/CD, model registry, versioning, and evaluation.
Establish best practices for model quality, bias detection, drift monitoring, LLM evaluation, hallucination mitigation, cost governance, and quota management.
Security, Privacy & Responsible AI
Architect secure AI systems with focus on IAM, service accounts, workload identity federation, VPC Service Controls, CMEK, and data encryption.
People & Technical Leadership
Lead and mentor senior AI architects, principal engineers, and technical leaders embedded within customer environments.
Establish architecture review boards and AI communities of practice.
Drive consistency of architecture, coding standards, and AI governance across accounts.
Coach leaders on executive communication, technical depth, and customer advisory skills.
Technical Expertise (Must-Have)
Expert-level Google Cloud Platform architecture including multi-project design, shared VPCs, networking, and security.
Deep proficiency in AI/ML and Generative AI technologies: Vertex AI (Gemini models, custom model training, Feature Store, Pipelines, Model Registry), Agentspace, agent design and orchestration, tool integration.
Strong experience in vector search (Vertex AI Vector Search, BigQuery vector search), data lakes and analytics (BigQuery, BigLake, Cloud Storage), streaming and event-driven systems (Pub/Sub, Dataflow).
API and microservices architectures (Apigee, Cloud Run, GKE).
DevOps, MLOps & Observability: CI/CD pipelines (Cloud Build, GitHub Actions, Jenkins), monitoring & observability (Cloud Monitoring, Cloud Logging), model performance and GenAI observability frameworks.
Infrastructure as Code: Terraform, Deployment Manager.
Google Document AI (Mandatory).
Experience & Qualifications
15+ years of overall technology experience.
8–10+ years in principle, enterprise, or chief architect roles.
Proven experience delivering large-scale AI / GenAI solutions on Google Cloud.
Strong background in customer-facing consulting or managed services delivery.
Demonstrated experience managing senior architects and technical leaders.
Prior role as Principal Architect, Distinguished Engineer, or Chief Architect preferred.
Leadership & Soft Skills
Strong executive presence and storytelling ability.
Ability to influence architecture and AI strategy at CXO level.
Hands-on technical depth with strategic thinking.
Passion for mentoring senior leaders and building AI talent pipelines.
Comfortable operating in complex, multi-stakeholder enterprise environments.
Certifications (Highly Desirable)
Google Cloud Certified – Professional Cloud Architect.
Google Cloud Certified – Professional Machine Learning Engineer.
Google Cloud Generative AI certifications.
TOGAF or equivalent architecture certification.
Work arrangement
No
More openings worth a look
Recently tracked roles with full details and direct application links.