Cloud Architect Solutions Data AI Modernization GCP

Job Description

**Cloud Architect Solutions (Data, AI & Modernization) Google Cloud**

Experience: 10–15 years overall, with 3–5+ years on Google Cloud
Location: Pan India
Role Type: Hands-on Solution Architecture | Sales Support | Multi-Domain Generalist

Role Overview

The Senior Cloud Architect – Solutions (Data, AI & Modernization) is a hands-on, broad-based solution architect responsible for designing and delivering end-to-end Google Cloud solutions spanning data platforms, AI workloads, application modernization, and cloud foundations.

This role is designed for a well-rounded Google Cloud architect who can flex across multiple solution domains and act as a force multiplier for Tech Mahindra’s Google Cloud solutions and sales support efforts. The role works closely with the Head of Google Cloud Solutions & Architecture and the AI SME architect, providing scale, coverage, and execution depth across customer engagements and solution initiatives.

Key Responsibilities

End-to-End Solution Architecture

• Design complete Google Cloud solutions covering data, AI, application, and platform layers
• Translate business requirements into holistic architectures rather than point solutions
• Balance architectural trade-offs across cost, performance, scalability, and security

Data and AI Solution Support

• Design and support data platforms using BigQuery, Dataflow, Pub/Sub, Dataproc, and Cloud Storage
• Support AI and GenAI solutioning including model integration, pipelines, and application integration
• Lead or support hands-on PoCs and pilots for data and AI use cases when required
• Collaborate closely with the AI SME on advanced AI solution builds and customer engagements

Application and Platform Modernization

• Architect application modernization solutions including containerization and re-platforming
• Design solutions using GKE, Cloud Run, and modern application services
• Support DevOps, CI/CD, and Infrastructure as Code implementation Design cloud foundations that support data, AI, and application workloads

Sales Support and Customer Engagement

• Support strategic sales pursuits and solution-led customer engagements
• Participate in customer workshops, discovery sessions, and architecture reviews
• Clearly explain solution architectures and trade-offs to technical and business stakeholders
• Work closely with sales teams to shape solution narratives and technical positioning

Google Cloud and Internal Collaboration

• Partner with Google Cloud architects and specialists across data, AI, and platform domains
• Support development of reusable solution assets, reference architectures, and accelerators
• Contribute to internal enablement and knowledge sharing across solution domains

Technical Skills and Expertise

Data Platforms

• Strong experience with BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage
• Understanding of data lakehouse and analytics architecture
• Experience integrating data platforms with applications and AI workloads

AI and GenAI

• Working hands-on experience with Vertex AI and GenAI solution patterns
• Ability to integrate AI models into applications and data workflows
• Understanding of AI lifecycle management, MLOps, and enterprise AI considerations

Application and Platform

• Hands-on experience with GKE, Cloud Run, and Compute Engine
• Experience with containerization, microservices, and API-driven architectures
• Understanding of DevOps pipelines and Infrastructure as Code practices

Cloud Foundations

• Solid understanding of networking, IAM, security, and governance on Google Cloud
• Experience designing scalable, secure, and cost-optimized cloud environments

Non-Technical and Soft Skills

• Strong systems thinking and solution integration mindset
• Ability to context switch across domains and priorities
• Clear communication and stakeholder engagement skills
• Comfort operating in fast-moving and ambiguous environments
• Collaborative mindset with strong ownership orientation

Qualifications and Certifications

• Bachelor’s or Master’s degree in Engineering or Computer Science
• Google Cloud Professional Architect or Professional Data Engineer preferred
• AI, Data, or Kubernetes certifications are a plus