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 youWhy 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 inferenceFirst 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 integrationFirst 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 skillsNice-to-Have:- AWS Certified Solutions Architect or AWS Certified SysOps Administrator- Exposure to AI/ML infrastructure (SageMaker, Bedrock)- Familiarity with Azure and GCP cloud environmentsWhy 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