Member of Technical Staff - Cloud & DevOps
Posted Updated
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