Member of Technical Staff - Cloud & DevOps

Power the Cloud Behind AI with goML 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 & Devops 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: 3+ 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