Senior Cloud Engineer

Job Description: Senior Cloud Engineer (Freelance)

Position: Senior Cloud Engineer (Freelance)

Experience: 5–8 years

Location: Remote (Client-facing role)

Engagement: Freelance / Contract

Company: Firecaat

About Firecaat

Firecaat is a fast-growing cloud consulting and solutions company specializing in delivering secure, scalable, and cost-efficient cloud-native architectures. We partner with clients across industries to design, build, and manage cloud platforms, with a strong focus on automation, DevOps, and modern data-driven solutions.

Role Overview

We are looking for a highly skilled Senior Cloud Engineer (Freelance) to join our team. The ideal candidate will have deep hands-on experience in AWS Cloud, Kubernetes (including bare metal deployments), and DevOps practices, with exposure to Machine Learning (ML), AI Ops, and Large Language Models (LLMs) being a strong advantage. This role is client-facing, requiring strong communication and consulting skills, as you will work closely with stakeholders on cloud-native ML/AI projects. This role involves regular communication with clients, including presenting technical solutions, leading workshops, and providing progress updates.

Key Responsibilities

• Design, deploy, and manage secure and scalable solutions on AWS Cloud, and on-premise environments including bare metal Kubernetes deployments.
• Build and manage Kubernetes (EKS) clusters and associated workloads, as well as Kubernetes on bare metal.
• Implement CI/CD pipelines and automation workflows to streamline deployments.
• Collaborate with data scientists and ML engineers to deploy and operationalize ML/AI models including those powered by LLMs, in production, leveraging containerization, CI/CD, and MLOps best practices.
• Apply AI Ops practices for monitoring, alerting, and predictive maintenance of cloud systems.
• Engage directly with clients to understand requirements, propose solutions, and deliver technical guidance.
• Ensure best practices in security, cost optimization, and performance tuning across cloud environments.

Required Skills & Experience

• 5–8 years of hands-on experience in AWS Cloud, including deep expertise in EC2, S3, IAM, VPC, Lambda, and container services (ECS/EKS).
• Strong expertise in Kubernetes (EKS or equivalent), containerization, and orchestration, including experience with bare metal Kubernetes deployments (e.g., using Kubespray, Rancher, or similar).
• Proficiency in DevOps practices including CI/CD, Infrastructure as Code (Terraform/CloudFormation), and GitOps (e.g., ArgoCD).
• Experience with monitoring, logging, and alerting tools (Prometheus, Grafana, ELK, CloudWatch).
• Good understanding of networking, security, and IAM in AWS and in on-premise environments.
• Experience collaborating directly with clients, translating business needs into technical solutions.

Added Advantage

• Experience in ML model deployment, ML pipelines, or MLOps frameworks such as Kubeflow, MLflow, or SageMaker Pipelines.
• Familiarity with modern observability and incident management tools.
• Experience with Feature stores
• Experience with deploying and managing LLMs (e.g., using Hugging Face Transformers, TensorFlow, or PyTorch)
• Experience with Kubernetes on Bare Metal environments

Soft Skills

• Excellent communication and presentation skills for client interactions.
• Ability to work independently in a freelance environment.
• Strong problem-solving and analytical mindset.
• Collaborative approach, with the ability to work in cross-functional teams.

What We Offer

• Opportunity to work with cutting-edge ML/AI cloud projects, including those leveraging LLMs.
• Flexible freelance/contract engagement.
• Exposure to multiple client environments and industries.
• Competitive freelance compensation model.

To Apply

Please submit your resume and a brief cover letter highlighting your relevant experience to

Job Type: Freelance

Pay: ₹50, ₹100,000.00 per month

Work Location: Remote

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