Senior Platform Engineer

Cashback24x7

India

Remote

INR 83,000 - 152,000

Part time

14 days+

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Job summary

Cashback24x7 is seeking a Senior Platform Engineer for a remote contractor role to shape production cloud infrastructure and platform engineering for AI training pipelines. You will own distributed systems, build containerized environments, and define performance and security requirements across deployments.

You should bring senior-level experience in cloud infra, DevOps, SRE, and hands-on expertise with IAM, networking, and observability.

Qualifications

  • Senior-level experience in cloud infra, platform engineering, DevOps, or SRE with ownership of a production platform.
  • Strong knowledge of distributed systems, scalable APIs, queues, autoscaling, and durable storage.
  • Hands-on with IAM, private networking, least-privilege security, and service-to-service security.
  • Experience with observability, measurable SLOs, rolling deployments, disaster recovery.

Responsibilities

  • Create realistic cloud infrastructure tasks involving distributed systems, networking, security, scalability, and reliability.
  • Build reproducible, containerized environments with valid reference solutions and intentionally defective variants.
  • Define measurable requirements across infrastructure configuration, deployed topology, and runtime behavior.
  • Develop deterministic integration, load, security, failure‑injection, deployment, and recovery tests.
  • Debug environments, document technical decisions, and review tasks created by other experts.

Skills

Senior cloud infra
Platform engineering
DevOps experience
SRE experience
Production ownership

Tools

Terraform
OpenTofu
AWS
Azure
GCP
Kubernetes

Job description

Job Description
Role Title: Senior Platform Engineer
Role Type: Contractor
Location: Remote

In this role, you'll apply your cloud infrastructure and platform engineering expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world engineering input. No prior experience in AI is required—your domain knowledge and hands‑on production experience are what matter.

Responsibilities
  • Create realistic cloud infrastructure tasks involving distributed systems, networking, security, scalability, and reliability.
  • Build reproducible, containerized environments with valid reference solutions and intentionally defective variants.
  • Define measurable requirements across infrastructure configuration, deployed topology, and runtime behavior.
  • Develop deterministic integration, load, security, failure‑injection, deployment, and recovery tests.
  • Debug environments, document technical decisions, and review tasks created by other experts.
Required Skills and Qualifications
  • Senior‑level cloud infrastructure, platform engineering, DevOps, systems engineering, or SRE experience, including personal ownership of a production platform.
  • Strong knowledge of distributed systems, scalable APIs, queues, autoscaling, durable storage, and partial‑failure scenarios.
  • Practical experience with IAM, private networking, least‑privilege access, and service‑to‑service security.
  • Experience with observability, measurable SLOs, rolling deployments, rollback strategies, and disaster recovery.
  • Ability to write infrastructure automation or testing tools and debug containerized environments using a relevant programming language.
Preferred Qualifications
  • Experience with Terraform or OpenTofu.
  • Experience with AWS, Azure, GCP, Kubernetes, or multi‑cloud infrastructure.
  • Experience building internal developer platforms, edge infrastructure, or shared platform services.
  • Experience with chaos engineering, fault injection, local cloud emulators, or resilience testing.
  • Experience creating technical evaluations, automated grading systems, or AI environments is helpful but not required.
Compensation Structure

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.

Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.

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