Pay Rate Range; $ 68.18 - 69.69/hr.
Job Description: Google Gen AI cloud| Databricks Architect
Must Have Technical/Functional 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
· GCP Expertise: Strong knowledge of GCP AI/ML services and infrastructure.
· AI/ML Frameworks: Proficiency with TensorFlow or PyTorch.
· Technical Skills: Experience with Python, data modeling, SQL, and APIs.
· Infrastructure as Code: Experience with Terraform for automation.
· Experience: 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 in Azure ADF
· 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
Roles & Responsibilities
· Architecture & Design: Design enterprise-grade AI platforms, including RAG (Retrieval Augmented Generation) and agentic solutions.
· GCP Implementation: Develop AI models using Vertex AI and Gemini, ensuring security and performance.
· Pipeline Development: Build and manage data pipelines, model lifecycle, CI/CD, and MLOps/LLMOps with Cloud Build and Vertex AI Pipelines.
· Cloud Infrastructure: Utilize GKE, Cloud Run, and BigQuery for robust application deployment.
· Strategy & Governance: Implement AI safety features, monitor model performance, and manage costs.
Generic Managerial Skills, If any
Experience working in agile development projects
Skills: AI & Gen AI - Products & Tools
Experience Required: 8-10 years
Skills
Category
Name
Importance
Experience
SkillCategoryTest1_MN
AI & Gen AI - Products & Tools
Yes
1
>7 years