Description

Key Responsibilities

Cloud Architecture & Strategy

• Design and implement enterprise-grade cloud architectures on GCP.
• Define cloud adoption roadmaps, migration strategies, and modernization initiatives.
• Drive architecture reviews and ensure alignment with GCP 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 GCP 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 Skills

Education

Bachelor's degree