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.
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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
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Preferred Certifications
•    Google Professional Cloud Architect
•    Google Professional Machine Learning Engineer
•    Google Professional Data Engineer
•    Google Professional Cloud DevOps Engineer
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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.
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Key Competencies
•    Strategic Thinking
•    Solution Architecture
•    Technical Leadership
•    Customer Engagement
•    Problem Solving
•    Innovation & AI Adoption
•    Stakeholder Management
•    Excellent Communication Skills

Key Skills

Education

Bachelor's degree