Sr Engineer - Cloud & Devops

Why You? Why Now?

What You?ll Do (Key Responsibilities)

First 30 Days: Strategic Onboarding

• Gain a deep understanding of goML?s AI/ML and GenAI architecture, pipelines, and infrastructure
• Assess existing cloud environments, DevOps practices, and deployment workflows
• Identify gaps, risks, and opportunities for optimization across infrastructure and processes
• Collaborate with engineering and leadership teams to align on priorities and roadmap

First 60 Days: Leadership & Execution

• Architect, design, and manage scalable AWS infrastructure across ECS, EKS, Lambda, EC2, VPC, S3, and API Gateway
• Lead the implementation and optimization of CI/CD pipelines (Jenkins, GitHub Actions, AWS CodePipeline)
• Establish Infrastructure as Code (IaC) standards using Terraform, AWS CDK, or CloudFormation
• Enable and optimize AI/ML workloads using services like AWS Bedrock and SageMaker
• Drive automation across infrastructure, deployments, and operational workflows
• Implement robust monitoring, alerting, and observability frameworks

First 180 Days: Ownership & Scale

• Own and evolve the DevOps and cloud architecture strategy for enterprise-scale AI deployments
• Drive performance optimization, cost efficiency, and system resilience initiatives
• Establish best practices for Kubernetes and container orchestration at scale
• Strengthen cloud security, governance, and compliance frameworks
• Mentor junior engineers and elevate DevOps maturity across teams
• Lead incident management, root cause analysis, and long-term reliability improvements

What You Bring (Qualifications & Skills)

Must-Have

• 8+ years of experience in Cloud/DevOps engineering roles
• Strong expertise in AWS cloud architecture and services (ECS, EKS, Lambda, EC2, VPC, API Gateway, S3, CloudWatch, Load Balancers)
• Proven experience designing and managing large-scale, production-grade cloud systems
• Deep hands-on experience with Infrastructure as Code (Terraform, AWS CDK, or CloudFormation)
• Strong proficiency in Docker and Kubernetes (designing and managing clusters at scale)
• Expertise in building and optimizing CI/CD pipelines
• Strong scripting/programming skills (Python, Bash)
• Solid understanding of cloud security, networking, observability, and reliability engineering
• Excellent problem-solving, stakeholder communication, and leadership skills

Nice-to-Have

• AWS Certified DevOps Engineer / Solutions Architect (Professional preferred)
• Experience with AI/ML infrastructure (AWS Bedrock, SageMaker)
• Certified Kubernetes Administrator (CKA)
• Experience with FinOps (cost optimization strategies)
• Exposure to multi-cloud or hybrid cloud environments

Why Work With Us?

• Remote-first culture with collaboration opportunities in Coimbatore
• Work on cutting-edge AI/ML & GenAI infrastructure challenges
• High ownership and impact in building enterprise-grade systems
• Competitive compensation, growth opportunities, and ESOPs