Sr DevOps Engineer

Purpose of Role:

Keyloop is seeking an experienced DevSecOps Engineer. As part of the product application development team you will be responsible for security, availability, latency, performance, efficiency, change management, monitoring, emergency response, and capacity planning. You will be working with a highly skilled team that is constantly seeking to improve existing application security, infrastructure, deployment automations and processes.

As a DevOps engineer you will be part of Engineering applications team responsible for engineering, enhancing, and transforming our AWS footprint, provide necessary operational support to multiple engineering teams. You will have chance to work on new cloud engineering standards and patterns and creating and supporting new tools and products.

Key Responsibilities:

• Provide necessary operational support to multiple platforms (both on-prem and on AWS)
• Create, maintain, and enhance monitoring, alerting, and debugging capabilities.
• Experience of setting up Monitoring, alerts and reports/dashboards for health/performance using tools such as CloudWatch, New Relic etc
• Automate build and deploy cloud platform solutions using AWS
• Perform technical troubleshooting for all AWS cloud environments.
• Maintaining, supporting, and enhancing CI/CD pipelines across all environments
• Design and implement AI-powered agents to detect deployment failures, recommend remediation, and safely automate deployment rollbacks with appropriate approval controls and auditability.
• Design, implement, and operate blue-green deployment models to enable zero-downtime releases, controlled traffic switching, rapid validation, and reliable rollback.
• Create and enhance AIOps capabilities for monitoring and observability, including anomaly detection, event correlation, alert-noise reduction, predictive insights, and automated incident response.
• Collaborate with Engineering teams to identify Platforms needs and issues.
• Build and maintain highly scalable, large-scale deployments globally.
• Ensure effective communication is maintained with necessary stakeholders.

Essentials Skills and Qualifications:

• • 5 years to 8 Years relevant work experience
  • Bachelor’s Degree, or equivalent experience in Engineering, Computer Science or Mathematics or related field
  • Understand customer issues, troubleshooting and documentation
  • Experience with AWS cloud infrastructure (EC2, ECS, EKS, RDS, Lambda, DynamoDB, Elastic Beanstalk etc)
  • CI/CD experience with GitHub Actions, Jenkins/Bamboo
  • Hands-on experience designing and implementing blue-green deployment strategies in AWS and containerized environments, including traffic switching, validation, and rollback procedures.
  • Practical experience building or integrating AI agents into CI/CD workflows for deployment health assessment, failure diagnosis, remediation recommendations, and automated rollback with human-in-the-loop controls.
  • Experience creating AIOps solutions for monitoring and observability using telemetry from logs, metrics, traces, and events to support anomaly detection, event correlation, predictive alerting, and automated incident response.
  • Understanding of web security and DevSecOps principles
  • Knowledge of microservice implementation technologies (both serverless and containers)
  • Strong communication and collaboration skills
  • Ability to work across global teams and working with different cultures across different time zones
  • Extensive experience working with IT security technologies, like firewalls, email security, web filtering, multi-factor authentication, identity and access management, privilege access management and web application security. Understanding SAST, DAST audits
  • Solid experience in network architecture, firewalls, VPN, PKI, encryption, common cloud platforms and security controls.
  • Working knowledge of applied cryptographic systems; TLS, encryption (at-rest, in-transit), key management
  • Experience with Atlassian tools stack - Jira, Confluence, Bitbucket

Essentials Technology Stack

• Terraform, CloudFormation, Serverless framework, AWS-CDK
• AWS (Lambda, API Gateway, SQS, SNS, DynamoDB, S3, EC2, WAF, IAM, VPC, EKS, ECS, Elastic Beanstalk, Cloudwatch etc)
• Github, Github actions, Jenkins, Docker, Ansible, Shell scripting
• JFrog Artifactory, Sonarcloud
• New Relic, Cloudwatch, ELK stack
• K8S, Helm
• Claude or equivalent enterprise AI tools and platforms (for example, Amazon Bedrock, Azure OpenAI, GitHub Copilot, n8n) for building AI agents, orchestrating automated workflows, integrating generative AI into DevOps processes, and supporting AIOps automation.