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-productive 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.
- Solid 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)

📌 GyanSys - AI Architect - Google Cloud Platform (Bengaluru)
🏢 GyanSys
📍 Bengaluru