Cloud Engineer
7 days ago
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 & OrientationDeep dive into goML’s AI/ML & GenAI workloads and cloud architecture patternsFamiliarize yourself with AWS environments, networking, and monitoring frameworks at goMLReview existing infrastructure and identify optimization opportunitiesShadow AI/ML teams to understand cloud requirements for model training and inferenceFirst 60 Days: Execution & ImpactDesign, deploy, and manage AWS infrastructure with services like EC2, ECS, EKS, Lambda, VPC, and RDSImplement cloud networking and security best practices (VPCs, IAM, API Gateway, Load Balancers)Automate infrastructure provisioning using Terraform, AWS CDK, or CloudFormationSet up observability and monitoring dashboards with CloudWatch and third-party toolsCollaborate with DevOps and AI/ML engineers to ensure seamless cloud integrationFirst 180 Days: Ownership & TransformationOwn cloud architecture for AI/ML and GenAI enterprise deploymentsOptimize infrastructure for performance, scalability, and cost-efficiencyBuild disaster recovery, backup, and high-availability strategiesEstablish best practices for cloud security, governance, and complianceMentor 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 expertiseHands-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 CloudFormationStrong understanding of cloud networking, IAM, and security best practicesExperience with monitoring, logging, and observability (CloudWatch, ELK, Grafana, etc.)Scripting experience (Python, Bash, or Shell) for automationExcellent troubleshooting and communication skillsNice-to-Have:AWS Certified Solutions Architect or AWS Certified SysOps AdministratorExposure 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 collaborationWork on cutting-edge AI/ML & GenAI cloud challenges at scaleDirect impact on enterprise cloud architecture and AI deploymentsCompetitive salary, leadership growth opportunities, and ESOPs down the line
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