GenAI & Databricks Architect

• 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).
• GCP Expertise:
  Strong knowledge of GCP AI/ML services and infrastructure.
• AI/ML Frameworks:
  Proficiency with Tensor Flow 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
• 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 Big Query for robust application deployment.
• Strategy & Governance:
  Implement AI safety features, monitor model performance, and manage costs.

• 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 Tensor Flow 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

• 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 Big Query for robust application deployment.
• Strategy & Governance:
  Implement AI safety features, monitor model performance, and manage costs.

Salary Range: $120,000 -$140,000 year

• Discretionary Annual Incentive.
• Comprehensive Medical Coverage:
  Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support:
  Maternal & Parental Leaves.
• Insurance Options:
  Auto & Home Insurance, Identity Theft Protection.
• Convenience & Professional Growth:
  Commuter Benefits & Certification & amp;
  Training Reimbursement.
• Time Off:
  Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance:
  Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

BACHELOR OF COMPUTER SCIENCE