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Open nowPosted 37 days ago

Member of Technical Staff - Cloud & DevOps

GoML16 open roles

Where
Coimbatore
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Your applicationOpen nowMember of Technical Staff - Cloud & DevOpsGoML · Coimbatore

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 37 days ago

The posting

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
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