Cloud Architect

Cloud Architect - Enterprise AI Platforms

Location: Mumbai | Onsite | Full-Time

About Network Science

At Network Science, we're not just deploying AI — we're building the Operating System for the Enterprise AI World. Our mission is to help global enterprises adopt, scale, and operationalize AI with precision, velocity, and measurable ROI.

To power this vision, we are seeking a Cloud Architect who can design, optimize, and future-proof our cloud-native infrastructure across multiple AI product lines — from GenAI co-pilots to multi-tenant SaaS platforms.

What You'll Do

As Cloud Architect, you'll be responsible for leading the design, deployment, and governance of all cloud infrastructure supporting our global product suite. You'll work closely with engineering, DevOps, data, and AI teams to ensure our infrastructure is secure, scalable, cost-optimized, and always production-ready.

Core Responsibilities:

• Architect and manage scalable, secure, and high-performance cloud environments (AWS/GCP/Azure) for AI-powered SaaS platforms
• Define and enforce cloud architecture best practices, standards, and frameworks for multi-region deployments
• Collaborate with engineering teams to build and scale microservices, containers, and serverless systems
• Oversee cloud security controls, IAM, encryption strategies, and compliance with frameworks like SOC2, ISO 27001, and GDPR
• Design and optimize network architecture, VPC peering, VPNs, and load balancing strategies
• Work with DevOps teams to implement CI/CD pipelines, observability tools, and auto-scaling mechanisms
• Lead cloud cost optimization efforts — balancing performance with budget
• Set up and manage backup, DR, failover, and high-availability strategies
• Provide technical leadership, mentoring, and architecture governance to cross-functional teams
• Stay ahead of emerging trends in cloud-native tools, AI infrastructure, and edge compute

Must-Have Qualifications

• 7–10 years of experience in cloud architecture, with proven delivery in SaaS or AI/ML product environments
• Deep expertise in AWS, with working knowledge of GCP or Azure
• Strong command over Kubernetes, Docker, Terraform/CloudFormation, and CI/CD automation
• Advanced understanding of cloud networking, storage, security, and IAM policies
• Experience with multi-tenant architecture, container orchestration, and API gateways
• Knowledge of AI/ML infrastructure needs, GPU provisioning, and hybrid training/inference workloads
• Ability to communicate complex concepts clearly and influence senior stakeholders
• Bachelor's or Master's in Computer Science, Information Systems, or related field
• Cloud certifications (e.g., AWS Certified Solutions Architect – Professional) are a strong plus

Preferred Qualifications

• Experience with multi-cloud or hybrid cloud strategy
• Exposure to LLM infrastructure or deploying ML inference pipelines at scale
• Familiarity with cloud-native databases (DynamoDB, BigQuery, Snowflake)
• Experience with monitoring and observability tools (Prometheus, Grafana, Datadog, etc.)
• Strong understanding of cloud compliance and audit readiness
• Prior experience in startup or high-growth environments with high deployment velocity
• Passion for automation, clean documentation, and platform thinking

Why This Role Matters

As Cloud Architect at Network Science, you will be building the invisible infrastructure that powers our AI innovation engine.

You will not just support deployments — you will enable transformation for some of the world's leading enterprises.

This is your opportunity to build systems that are mission-critical, globally scalable, and AI-native by design.