AWS Cloud Consultant

r3 Consultant; Bengaluru; On-site; INR 800,000 - 1,200,000; Full time

Job summary

r3 Consultant is seeking a Mid-Level Cloud Engineer based in Bengaluru, Karnataka, with hands-on experience in AWS, Kubernetes, and modern cloud-native practices. The ideal candidate will design scalable infrastructure, manage CI/CD pipelines, and collaborate with engineering teams for system reliability. This role requires a strong understanding of distributed systems, a problem-solving mindset, and a passion for continuous learning. Experience in programming and Infrastructure-as-Code tools is essential.

Qualifications

• 3–6 years of professional experience in Cloud Engineering, Platform Engineering, or DevOps.
• Strong troubleshooting, debugging, and automation skills.
• Ability to work independently in fast-paced and evolving environments.

Responsibilities

• Design, build, and maintain scalable Kubernetes-based infrastructure on AWS.
• Manage and improve CI/CD pipelines, observability, platform reliability, security, and cost optimization.
• Collaborate closely with engineering teams to ensure system reliability.

Skills

AWS cloud services

Kubernetes cluster management

Go

Python

TypeScript

Infrastructure-as-Code tools

CI/CD pipelines

Linux systems

Networking concepts

Tools

Terraform

Pulumi

AWS CDK

Job description

About The Role

We are looking for a Mid-Level Cloud Engineer with strong hands‑on experience in AWS, Kubernetes, and modern cloud‑native engineering practices. This role is ideal for engineers who enjoy solving real infrastructure and platform challenges, building scalable systems, and working across both platform and application engineering.

The ideal candidate understands how distributed systems operate end‑to‑end and can confidently troubleshoot, automate, and improve production environments. We value engineers who focus on fundamentals, adaptability, ownership, and continuous learning over dependency on specific tools or frameworks.

Key Responsibilities

• Design, build, and maintain scalable Kubernetes‑based infrastructure on AWS.
• Manage and improve CI/CD pipelines, observability, platform reliability, security, and cloud cost optimization.
• Develop internal tools, automation workflows, controllers, operators, and supporting platform services.
• Deploy and support AI‑driven services and applications in production environments.
• Work across multi‑cloud or customer‑specific environments when required.
• Automate manual operational processes and continuously improve platform efficiency.
• Collaborate closely with engineering teams to ensure system reliability, scalability, and maintainability.
• Troubleshoot infrastructure, networking, deployment, and distributed system issues across environments.

Required Skills & Experience

• 3–6 years of professional experience in Cloud Engineering, Platform Engineering, or DevOps.
• Strong production experience with AWS cloud services.
• Hands‑on expertise in Kubernetes cluster management, troubleshooting, networking, and container orchestration.
• Strong programming skills in at least one language such as Go, Python, or TypeScript.
• Good understanding of Linux systems, networking concepts, and distributed application architecture.
• Experience with Infrastructure‑as‑Code tools such as Terraform, Pulumi, or AWS CDK.
• Experience building and maintaining CI/CD pipelines and observability platforms.
• Strong troubleshooting, debugging, and automation skills.
• Ability to work independently in fast‑paced and evolving environments.

Preferred Qualifications

• Experience with platform engineering and cloud‑native architectures.
• Exposure to AI/ML deployment environments or AI agent infrastructure.
• Experience contributing to internal tools, open‑source projects, or side projects.
• Strong mindset toward continuous learning, ownership, and operational excellence.

What We Value

• Strong engineering fundamentals and problem‑solving mindset.
• Curiosity and willingness to learn new technologies quickly.
• Ownership, accountability, and collaborative working style.
• Focus on practical solutions, automation, and continuous improvement.
• Ability to work effectively in environments with ambiguity and rapid iteration.