Role Overview:This role focuses on the design, delivery, and implementation of enterprise-grade AI platforms and solutions primarily on Google Cloud Platform (GCP), with significant involvement in large-scale data migration and pipeline development on Azure. The architect will be responsible for developing AI models, managing data pipelines, and ensuring robust cloud infrastructure.
Key Responsibilities:- Design enterprise-grade AI platforms, including RAG (Retrieval-Augmented Generation) and agentic solutions.
- Develop AI models using Vertex AI and Gemini, ensuring security and performance on GCP.
- Build and manage data pipelines, model lifecycle, CI/CD, and MLOps/LLMOps with Cloud Build and Vertex AI Pipelines.
- Utilize GKE, Cloud Run, and BigQuery for robust application deployment.
- Implement AI safety features, monitor model performance, and manage costs.
Required Skills:- Design, delivery, and implementation of Google Cloud Platform (GCP) infrastructure and solutions.
- Architect design and implement large-scale migration pipelines from on-prem systems to Azure Data Lake Storage (ADLS).
- Architect experience in generating data pipelines in Azure ADF.
- Strong knowledge of GCP AI/ML services and infrastructure.
- Proficiency with TensorFlow or PyTorch.
- Experience with Python, data modeling, SQL, and APIs.
- Experience with Terraform for automation.
- Proven ability in delivering AI/ML solutions in a cloud environment.
- Experience with performing analytics on data for stakeholders.
- Experience in ingesting data from different sources using Azure ADF.
- Ability to ensure reliable handling of high-volume unstructured data with performance and cost efficiency.
- Implement data quality checks, logging, and traceability to support audit and compliance needs.
- Experience in transforming data using Azure Databricks & Delta lake.
- Google Gen AI cloud expertise.
- Databricks Architect experience.
Qualifications:Preferred Skills:- Experience working in agile development projects.
