About the role

Power the Cloud Behind AI with goMLAt 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

Member of Technical Staff - Cloud & DevOps

About the role

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