(Apply in 3 Minutes) Cloud Engineer

At goML, we design and build cutting-edge Generative AI, AI / ML, and Data Engineering solutions that help businesses unlock the full potential of their data, drive intelligent automation, and create transformative AI-powered experiences. Our mission is to bridge the gap between state-of-the-art AI research and real-world enterprise applications – helping organizations innovate faster, make smarter decisions, and scale AI solutions seamlessly.

We’re looking for a Cloud Engineer with strong AWS expertise and hands-on experience in designing, deploying, and optimizing scalable cloud environments. In this role, you’ll architect and manage secure, cost-efficient, and high-performance cloud infrastructure that powers AI / ML and GenAI solutions at enterprise scale. If you thrive in solving complex cloud challenges and enabling teams with reliable, cloud-native systems, we’d love to hear from you!

Why You? Why Now?

As AI adoption accelerates, cloud infrastructure becomes the foundation that enables enterprises to scale their AI / ML workloads. This role is ideal for someone who loves building cloud-native architectures, optimizing infrastructure, and ensuring cloud environments are production-ready for AI.

What You’ll Do (Key Responsibilities)

First 30 Days : Foundation & Orientation
• Deep dive into goML’s AI / ML & GenAI workloads and cloud architecture patterns
• Familiarize yourself with AWS environments, networking, and monitoring frameworks at goML
• Review existing infrastructure and identify optimization opportunities
• Shadow AI / ML teams to understand cloud requirements for model training and inference

First 60 Days : Execution & Impact
• Design, deploy, and manage AWS infrastructure with services like EC2, ECS, EKS, Lambda, VPC, and RDS
• Implement cloud networking and security best practices (VPCs, IAM, API Gateway, Load Balancers)
• Automate infrastructure provisioning using Terraform, AWS CDK, or CloudFormation
• Set up observability and monitoring dashboards with CloudWatch and third-party tools
• Collaborate with DevOps and AI / ML engineers to ensure seamless cloud integration

First 180 Days : Ownership & Transformation
• Own cloud architecture for AI / ML and GenAI enterprise deployments
• Optimize infrastructure for performance, scalability, and cost-efficiency
• Build disaster recovery, backup, and high-availability strategies
• Establish best practices for cloud security, governance, and compliance
• Mentor junior engineers and influence long-term multi-cloud strategies (AWS, Azure, GCP)

What You Bring (Qualifications & Skills)

Must-Have :
• 2-4 years of experience in cloud engineering with strong AWS expertise
• Hands-on experience with core AWS services (EC2, VPC, S3, RDS, Lambda, ECS, EKS, API Gateway, Load Balancers)
• Proficiency with IaC tools like Terraform, AWS CDK, or CloudFormation
• Strong understanding of cloud networking, IAM, and security best practices
• Experience with monitoring, logging, and observability (CloudWatch, ELK, Grafana, etc.)
• Scripting experience (Python, Bash, or Shell) for automation
• Excellent troubleshooting and communication skills

Nice-to-Have :
• AWS Certified Solutions Architect or AWS Certified SysOps Administrator
• Exposure to AI / ML infrastructure (SageMaker, Bedrock)
• Familiarity with Azure and GCP cloud environments

Why Work With Us?
• Remote-first, with offices in Coimbatore for in-person collaboration
• Work on cutting-edge AI / ML & GenAI cloud challenges at scale
• Direct impact on enterprise cloud architecture and AI deployments
• Competitive salary, leadership growth opportunities, and ESOPs down the line