Enterprise AI Platform Architect

Deloitte France

Tempe (AZ)

Presencial

USD 122.000 - 241.000

Jornada completa

14 días+

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Descripción de la vacante

Google is seeking an AI Architect to lead the design and deployment of enterprise AI platforms and applications on Google Cloud. You will architect end-to-end data pipelines, model lifecycles, APIs and CI/CD/MLOps workflows using Vertex AI, Gemini, and Terraform.

The role emphasizes security, governance, and scalable production readiness. Required qualifications include 6+ years as a software/solution architect with 5+ years on Google Cloud, plus 2+ years in containerized workloads on GKE and 2+

Formación

Bachelor's degree in Computer Science, Engineering or a related technical field.

Responsabilidades

Architect and Design: Design and development of enterprise-grade AI applications and platforms, with a focus on scaling AI solutions for production.
LLM and AI Integration: Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications.
Enterprise Architecture: Collaborate with enterprise architects to ensure AI solutions align with the broader company's technical strategy, governance, and standards.
Cloud and GenAI Native Development: Design and deploy applications using Cloud Native principles on a hyperscaler platform.
Security & Governance: Ensure the security of all AI/ML systems by addressing potential vulnerabilities.
Design Patterns: Apply and enforce Application Design Patterns and Agentic Design Patterns to build resilient software systems.
Required Qualifications
Bachelor's degree in Computer Science, Engineering or a related technical field.
6+ years' experience as a Software or Solution Architect, with a strong focus on production readiness.
5+ years hands-on with Google Cloud, including 2+ end-to-end enterprise implementations in production.
4+ years designing and implementing Google Cloud networks, security controls, and landing zones using Terraform.
2+ years building and operating containerized workloads on GKE (autoscaling, ingress, monitoring/observability).
2+ years implementing CI/CD and DevSecOps with Cloud Build, GitHub Actions, or Jenkins.
3+ years executing migration or modernization programs to Google Cloud (rehost, replatform, refactor).
2+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, including 1+ years' production deployment (e.g. RAG with Vertex AI Search/Vector Search, prompt design, safety policies, observability).
Deep understanding of AI/ML concepts, including experience with LLMs and their application in enterprise settings.
Experience implementing multiple AI solutions in a professional, real-world environment.
Strong understanding of security implications related to AI/ML systems (e.g., data privacy, model poisoning, adversarial attacks).
Familiarity with various hyperscaler tools and services.
Hyperscaler Architect certification is required (e.g., AWS Certified Solutions Architect, Azure Solutions Architect Expert, or GCP Professional Cloud Architect).
Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serve.
Limited immigration sponsorship may be available.
Preferred Qualifications: Google Professional Machine Learning Engineer certification or the equivalent ML certification.
Master's degree in technology-related discipline.
2+ years's leading high performance, results driven engineering teams delivering AI platforms or applications.
1+ year implementing LLMOps/MLOps using Vertex AI Pipelines and Cloud Build (or similar)