Senior Google Cloud Architect

Employment Eligibility Statement
Due to specific project and client requirements, this position is open to U.S. Citizens and U.S. Lawful Permanent Residents (s) . Sponsorship is not available at this time. Danta Technologies evaluates all candidates in compliance with the Immigration and Nationality Act (INA) and EEOC guidelines . All hiring decisions are made without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic.



TITLE : Senior Google Cloud Architect – Google Cloud Platform (Google Cloud Platform) & AI Services
Location – Milpitas, CA (Onsite/Hybrid)

Primary - GKE cluster with TPU configuration

Experience:

• 10+ years of overall IT experience with 6+ years in Google Cloud Platform (Google Cloud Platform) and proven expertise in designing, deploying, and operating enterprise-scale cloud and AI solutions.

Job Summary:

We are seeking a highly experienced Senior Google Cloud Architect to lead cloud transformation, modernization, and AI initiatives on Google Cloud Platform (Google Cloud Platform). The candidate will be responsible for designing scalable cloud architectures, enabling AI-driven business solutions, guiding migration and modernization programs, and providing technical leadership across multi-disciplinary teams.

The ideal candidate should possess deep expertise in Google Cloud services, cloud-native architectures, data and AI platforms, MLOps, security, governance, and enterprise-scale implementation of Generative AI solutions.

Key Responsibilities:

Cloud Architecture & Strategy

• Design and implement enterprise-grade cloud architectures on Google Cloud Platform.
• Define cloud adoption roadmaps, migration strategies, and modernization initiatives.
• Drive architecture reviews and ensure alignment with Google Cloud Platform best practices and Well-Architected Framework principles.
• Provide technical leadership for cloud-native application development and modernization.

AI & Machine Learning Solutions

• Architect and deploy AI/ML solutions leveraging Google Cloud AI services.
• Design Generative AI, LLM, RAG (Retrieval-Augmented Generation), and intelligent automation platforms.
• Implement AI governance, responsible AI practices, model lifecycle management, and monitoring.
• Collaborate with business stakeholders to identify and deliver AI-powered use cases.

Data & Analytics

• Design modern data platforms using Google Cloud Platform data services.
• Implement scalable data pipelines, data lakes, and analytics solutions.
• Enable AI and machine learning workloads through robust data architectures.

Security & Governance

• Establish cloud security, compliance, identity management, and governance controls.
• Ensure adherence to enterprise security standards and regulatory requirements.
• Drive cost optimization, operational excellence, and reliability initiatives.

Leadership & Stakeholder Management

• Act as a trusted advisor for customers and leadership teams.
• Mentor architects, engineers, and cloud practitioners.
• Support pre-sales activities, solution proposals, and customer workshops.
• Lead cross-functional teams and oversee successful program execution.

Mandatory Technical Skills:

Google Cloud Platform

• Google Compute Engine (GCE)
• Google Kubernetes Engine (GKE)
• Cloud Run
• Cloud Functions
• VPC, Networking & Load Balancing
• Cloud Storage
• Cloud SQL
• Big Query
• Pub/Sub
• Cloud Monitoring & Logging
• IAM & Security Services
• Terraform / Infrastructure as Code

Google AI & Machine Learning Services

• Vertex AI
• Vertex AI Studio
• Gemini Models
• AutoML
• AI Platform
• Document AI
• Vision AI
• Speech-to-Text
• Natural Language AI
• AI Agents & Conversational AI

Generative AI

• Large Language Models (LLMs)
• Prompt Engineering
• RAG Architectures
• Vector Databases
• AI Agents & Agentic Frameworks
• LangChain / Similar AI Orchestration Frameworks

DevOps & Automation

• CI/CD Pipelines
• GitHub / GitLab
• Cloud Build
• Docker
• Kubernetes
• MLOps Practices

Programming Languages

• Python (Mandatory)
• Java or Go (Preferred)
• SQL

Preferred Certifications:

• Google Professional Cloud Architect
• Google Professional Machine Learning Engineer
• Google Professional Data Engineer
• Google Professional Cloud DevOps Engineer

Desired Experience:

• Enterprise cloud migration and modernization programs.
• AI/GenAI implementation for business transformation.
• Semiconductor, Manufacturing, Hi-Tech, Financial Services, or Retail industry experience.
• Multi-cloud exposure (AWS / Azure) is an added advantage.
• Experience working with global stakeholders and large-scale transformation programs.

Key Competencies:

• Strategic Thinking
• Solution Architecture
• Technical Leadership
• Customer Engagement
• Problem Solving
• Innovation & AI Adoption
• Stakeholder Management
• Excellent Communication Skills

Notes:- All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

Benefits: Danta offers a compensation package to all W2 employees that are competitive in the industry. It consists of competitive pay, the option to elect healthcare insurance (Dental, Medical, Vision), Major holidays and Paid sick leave as per state law.

The rate/ Salary range is dependent on numerous factors including Qualification, Experience and Location.