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