Description :

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.

Were looking for a Cloud Engineer with strong AWS expertise and hands-on experience in designing, deploying, and optimizing scalable cloud environments.

In this role, youll 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, wed 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 Youll Do :

First 30 Days : Foundation & Orientation :

- Deep dive into goMLs 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 :

- 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 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