Junior SRE/DevOps Engineer

algoleap; Hyderabad; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Algoleap is seeking a Junior SRE/DevOps Engineer to support infra, CI/CD, and key projects globally under guidance from senior engineers.

You will work in a distributed team, leveraging AWS, Terraform, and container technologies to build scalable cloud infrastructure and automated deployment pipelines. Strong communication and analytical skills are essential.

Qualifications

• 2-4 years of experience building and maintaining AWS infrastructure (VPC, EC2, IAM, S3, RDS, Lambda).
• Terraform experience to manage infrastructure as code.
• Hands-on with Docker and Kubernetes for containerized apps.
• Experience with CI/CD tools (GitHub, Jenkins, Azure DevOps).
• Scripting with Python, Bash, or PowerShell.
• Familiarity with ELK stack and monitoring tools.

Responsibilities

• Assist in designing and maintaining scalable, secure AWS infrastructure.
• Collaborate with software teams to define deployment requirements.
• Provision and manage AWS resources using IaC (Terraform).
• Containerize and orchestrate with Docker and Kubernetes.
• Troubleshoot issues across services and improve monitoring.

Skills

AWS

Terraform

Docker

Kubernetes

Python

CI/CD

Linux/Windows

Jenkins

Azure DevOps

ELK

Tools

GitHub

Jenkins

Azure DevOps

Datadog

ElasticSearch

Kibana

Prometheus

Job description

As a Junior SRE/DevOps Engineer, you will support the setup and maintenance of Infra, CI/CD and help sustain different key projects used throughout globally, working under the guidance of senior engineers.

As a member of our geographically distributed development team your communication and analytical skills are essential to the role.

Key Responsibilities

• Assist in designing and maintaining cloud infrastructure that is secure, scalable, and highly available on AWS/Azure
• Work collaboratively with software engineering to define infrastructure and deployment requirements
• Provision, configure and maintain AWS cloud infrastructure defined as code.
• Containerization using Docker and Kubernetes
• Troubleshoot problems across a wide array of services and functional areas
• Build and maintain operational tools for deployment, monitoring, and analysis of AWS infrastructure and systems
• Assist with infrastructure cost analysis and support optimization efforts.
• Support the development of self-healing and automated remediation mechanisms using AI/ML techniques
• Assist in integrating AI/LLM capabilities into DevOps workflows (e.g., log analysis, automated RCA, deployment insights)
• Support monitoring strategy enhancements by leveraging intelligent alerting, noise reduction, and pattern-based anomaly detection across logs, metrics, and traces.
• Assist in building and maintaining MLOps pipelines for model training, deployment, and continuous improvement.
• Collaborate with a global team of engineers in a highly agile DevOps environment, focused on efficient operation of daily activities, developer productivity and continuous improvement of the framework.
• Support the development, implementation, and maintenance of CI/CD frameworks, and contribute to tools development for hybrid environments (Cloud, On premise) with a vision to achieve “CI/CD” objectives for large-scale integration of systems in order to reduce manual build and deploy efforts.
• Work with geographically dispersed teams including multi-vendor into Scrum teams to meet “CI/CD”

Required Knowledge & Skills

• 2-4 years of experience building and maintaining AWS infrastructure (VPC, EC2, Security Groups, IAM, ECS/EKS, CloudFront, S3, RDS, SQS, SNS, Lambda Function, Batch jobs, AWS Glue)
• Working understanding of how to secure AWS environments and meet compliance requirements
• Working knowledge of deploying and managing infrastructure with Terraform.
• Exposure to or working knowledge of LLMs (OpenAI, Azure OpenAI, Claude etc.)
• Basic awareness of LLMOps concepts (prompt management, model evaluation, versioning, fine-tuning lifecycle)
• Familiarity with MLOps tools such as MLflow, SageMaker, Kubeflow or equivalent.
• Familiarity with AIOps platforms/tools for intelligent monitoring and incident management.
• Ability to apply AI techniques to improve deployment speed, reliability, and monitoring effectiveness.
• Working experience on windows & Linux based environments.
• Experience with Docker, GitHub, Jenkins, Azure DevOps, ELK and deploying applications on AWS.
Good command on scripting languages like Python, Bash/Shell, Powershell etc
• Knowledge in log analytics tools like Elastic search and Kibana.
• Basic knowledge of Cloud Migration/Disaster Recovery/Blue Green Deployment implementation.
• Good understanding about monitoring the services and alerting using Cloudwatch, Datadog, Prometheus or Azure monitor.
• Good to hire a candidate with certification

Personal Attributes

• Very good communication skills.
• Ability to easily fit into a distributed development team.
• Customer service oriented.
• Enthusiastic/High initiative.
• Ability to manage timelines of multiple initiatives.
• Very good attention to detail and the ability to always follow up.