Live opening · Posted 1 day ago
At a glance
The key details from the original listing.
About the role
Description supplied by the original job listing.
Job Description
We are looking for an experienced GCP AI Architect to design, implement, and govern enterprise-scale cloud and artificial intelligence solutions on Google Cloud Platform (GCP). The ideal candidate will have strong expertise in GCP services, Vertex AI, Generative AI, cloud-native architecture, and MLOps, with the ability to build scalable, secure, and cost-efficient AI platforms.
Key Responsibilities
Design and architect enterprise-scale cloud and AI solutions on Google Cloud Platform.
Leverage GCP services, including Compute Engine, Google Kubernetes Engine (GKE), Cloud Run, BigQuery, Cloud Storage, Pub/Sub, and Dataflow.
Architect and implement AI/ML solutions using Vertex AI, Gemini, Generative AI, and Retrieval-Augmented Generation (RAG).
Design and implement scalable AI platforms, microservices, and cloud-native applications.
Establish MLOps practices for model deployment, monitoring, automation, and lifecycle management.
Lead cloud migration, modernization, and enterprise AI transformation initiatives.
Implement infrastructure automation using Terraform and establish CI/CD and DevSecOps pipelines.
Define cloud architecture standards, governance frameworks, and best practices.
Ensure cloud security through effective IAM, networking, access controls, and security policies.
Optimize cloud infrastructure performance, scalability, reliability, and operational costs.
Collaborate with engineering, data science, DevOps, and business teams to deliver enterprise AI solutions.
Drive FinOps practices and cloud cost optimization across cloud and AI workloads.
Required Skills
10+ years of experience in cloud architecture, solution architecture, or related technical roles.
Strong hands-on expertise in Google Cloud Platform (GCP) services and architecture.
Experience with Compute Engine, GKE, Cloud Run, BigQuery, Cloud Storage, Pub/Sub, and Dataflow.
Strong knowledge of Vertex AI, Gemini, Generative AI, and RAG architectures.
Experience designing and implementing MLOps pipelines and AI/ML platforms.
Expertise in cloud-native architecture, microservices, Kubernetes, and distributed systems.
Proficiency in Terraform, CI/CD automation, and DevSecOps practices.
Strong understanding of cloud networking, IAM, security, governance, and compliance.
Experience with cloud migration, modernization, scalability, and performance optimization.
Preferred Qualifications
Programming experience with Python and/or Java.
Experience with API development and integration.
Knowledge of FinOps and cloud cost management practices.
Exposure to multi-cloud environments.
Google Professional Cloud Architect certification is preferred.
(ref:hirist.tech)
Work arrangement
No
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