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