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Open nowPosted 7 hours ago

Cloud Infrastructure & Platform Engineer

Virallens

Where
Bengaluru, KA, India
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Your applicationOpen nowCloud Infrastructure & Platform EngineerVirallens · Bengaluru, KA, India

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Virallens's own form.

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The clock on this job

Early applications get read.

13.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.1%7 days
  4. 21.1%14 days
  5. 35.8%30 days
  6. 59.0%60 days
This job: posted 7 hours ago

The posting

Cloud Infrastructure & Platform Engineer

📍 Location: Bengaluru, Karnataka (On-site) 💼 Employment Type: Full-time 🧑‍💻 Experience: 3–6 Years

About the Role

As a Cloud Infrastructure & Platform Engineer, you will design, build, and operate the cloud infrastructure that powers our AI products and enterprise applications.

You'll own infrastructure architecture across cloud platforms, networking, Kubernetes, security, scalability, observability, and platform services while enabling engineering teams to build and deploy applications efficiently.

Rather than focusing only on deployments, you'll architect reliable, secure, and scalable infrastructure that supports production workloads, AI services, and modern SaaS platforms.

You'll work closely with Engineering, AI, and Product teams to design infrastructure that balances performance, reliability, security, and cost.

What You'll Do

☁️ Cloud Infrastructure & Platform Architecture

  • Design cloud-native infrastructure on AWS or GCP for scalable production applications.
  • Architect Kubernetes platforms that support microservices, AI workloads, APIs, and enterprise applications.
  • Design secure networking including VPCs, subnets, private networking, VPNs, load balancers, gateways, and DNS.
  • Build reusable infrastructure using Infrastructure as Code (Terraform).
  • Design highly available, fault-tolerant, and disaster-resilient cloud architectures.
  • Define infrastructure standards, governance, and platform best practices.
  • Design multi-environment infrastructure for development, staging, and production.

🏗 Application Infrastructure

  • Design infrastructure for containerized applications using Kubernetes and Docker.
  • Architect application networking, ingress, service discovery, storage, and scaling strategies.
  • Build infrastructure supporting REST APIs, event-driven systems, background workers, and distributed services.
  • Design infrastructure for databases, Redis, Kafka, object storage, and messaging systems.
  • Support multi-tenant SaaS architectures with secure tenant isolation.
  • Optimize infrastructure for performance, scalability, availability, and operational efficiency.

🔒 Security & Reliability

  • Implement cloud security best practices including IAM, secrets management, encryption, network security, and compliance.
  • Design monitoring, logging, alerting, tracing, and operational dashboards.
  • Improve resilience through backup, disaster recovery, failover, and capacity planning.
  • Perform infrastructure reviews, architecture improvements, and production readiness assessments.
  • Optimize cloud resource utilization and infrastructure costs.

🚀 Platform Engineering & Automation

  • Build internal platforms that simplify infrastructure provisioning and deployments.
  • Create reusable Terraform modules and platform templates.
  • Improve developer experience through automation and self-service infrastructure.
  • Enhance CI/CD pipelines where required to support reliable infrastructure delivery.
  • Standardize infrastructure provisioning across engineering teams.

🤖 AI Infrastructure (Preferred)

  • Design infrastructure supporting AI inference, RAG systems, vector databases, and LLM services.
  • Build scalable GPU-enabled infrastructure where required.
  • Support AI workloads with efficient networking, storage, monitoring, and autoscaling.

What We're Looking For

Required Skills

  • 3–6 years of experience designing and managing cloud infrastructure.
  • Strong experience with AWS or GCP architecture.
  • Hands-on experience designing Kubernetes platforms in production.
  • Expertise in Infrastructure as Code using Terraform.
  • Strong understanding of networking, VPC design, routing, DNS, VPNs, firewalls, and load balancing.
  • Experience designing scalable cloud architectures for distributed applications.
  • Knowledge of Linux, Docker, Kubernetes, and cloud-native technologies.
  • Experience designing highly available, fault-tolerant systems.
  • Strong understanding of infrastructure security and cloud best practices.
  • Experience with monitoring, observability, and platform reliability.
  • Excellent troubleshooting and architecture skills.

Nice to Have

  • Experience designing infrastructure for AI/ML platforms.
  • Experience with Vertex AI, SageMaker, or GPU infrastructure.
  • Multi-cloud experience (AWS, GCP, Azure).
  • Experience with service mesh technologies (Istio, Linkerd).
  • Experience building Internal Developer Platforms (IDP).
  • Knowledge of FinOps and cloud cost optimization.
  • Experience with large-scale SaaS infrastructure.

What You'll Build

You'll design and build cloud-native infrastructure, Kubernetes platforms, secure networking, AI infrastructure, scalable application platforms, observability systems, and reusable cloud foundations that power production AI applications and enterprise software.

What Will Help You Succeed

We're looking for someone who:

  • Thinks in terms of platform and infrastructure architecture, not just deployments.
  • Designs scalable, secure, and resilient systems.
  • Takes ownership of cloud infrastructure end-to-end.
  • Balances reliability, performance, security, and cost.
  • Collaborates effectively with Software, AI, and Product teams.
  • Continuously improves platform capabilities and developer experience.

What Success Looks Like

Within your first few months, you'll:

  • Design scalable cloud infrastructure for production applications.
  • Improve Kubernetes architecture and platform reliability.
  • Establish reusable infrastructure standards and IaC practices.
  • Strengthen infrastructure security, observability, and resilience.
  • Optimize cloud performance and operational costs.
  • Become the go-to infrastructure architect for Engineering and AI teams.
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