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Company Description
NEXUS AIDC is revolutionizing the data center industry with an AI-native Data Center Operating System. Addressing the growing complexity of AI-driven workloads and infrastructure, our platform unifies DCIM, APM, FinOps, Kubernetes orchestration, AI workload management, digital twins, and full-stack observability into one intelligent, real-time system.
With predictive intelligence and automated remediation, NEXUS enables organizations to optimize infrastructure performance, improve resource utilization, and manage AI workloads more efficiently
Role Description
This is a full-time, on-site DevOps Engineer role based in Bengaluru for professionals with approximately 2–3 years of experience. The DevOps Engineer will design, implement, and maintain CI/CD pipelines that support rapid, reliable delivery of platform features and infrastructure changes.
Key Responsibilities
Kubernetes & Container Management: Deploy, configure, monitor, and troubleshoot containerized applications using Docker and Kubernetes, including managing pods, services, deployments, and cluster resources.
CI/CD Automation: Develop, maintain, and improve CI/CD pipelines using GitHub Actions, GitLab CI/CD, or Jenkins, ensuring efficient and reliable application deployments.
Infrastructure as Code (IaC): Implement and maintain infrastructure automation using Terraform, Ansible, or equivalent tools across cloud and on-premises environments.
Linux & Infrastructure Administration: Manage Linux-based servers, system configurations, networking, access controls, patching, and routine infrastructure maintenance.
Monitoring & Observability: Configure and maintain monitoring, logging, and alerting solutions using Prometheus, Grafana, ELK, or similar tools to improve system visibility and reliability.
Automation & Scripting: Develop Bash or Python scripts to automate operational processes, reduce manual intervention, and improve infrastructure efficiency.
Troubleshooting & Performance: Identify and resolve deployment, infrastructure, networking, and application performance issues, collaborating with senior engineers on complex incidents.
Cloud & AI Infrastructure: Support infrastructure deployments across cloud, hybrid, and on-premises environments, including Kubernetes-based AI workloads and GPU-enabled infrastructure.
Security & Reliability: Follow DevSecOps practices, including access management, secrets handling, configuration management, and infrastructure security.
Collaboration & Documentation: Work closely with development, QA, and infrastructure teams to improve deployment processes, operational reliability, and technical documentation.
Qualifications
Immediate availability to join is mandatory.
2–3 years of hands-on experience in DevOps, SRE, cloud infrastructure, or infrastructure engineering.
Strong working knowledge of Linux administration, networking fundamentals, and system troubleshooting.
Practical experience with Docker and Kubernetes, including application deployments, troubleshooting, and cluster operations.
Hands-on experience implementing and maintaining CI/CD pipelines using GitHub Actions, GitLab CI/CD, or Jenkins.
Working knowledge of Terraform, Ansible, or similar infrastructure automation tools.
Proficiency in scripting using Bash or Python.
Experience with monitoring and observability tools such as Prometheus, Grafana, or ELK.
Familiarity with Git, container registries, deployment workflows, and release management.
Understanding of cloud infrastructure concepts and experience with at least one major cloud platform (AWS, Azure, or GCP).
Strong troubleshooting skills and the ability to independently resolve routine infrastructure and deployment issues.
Good communication skills, ownership mindset, and ability to work collaboratively in a fast-paced engineering environment.
Preferred / Good-to-Have Skills
Exposure to GPU infrastructure, NVIDIA GPU operators, device plugins, or GPU monitoring.
Familiarity with AI/ML workloads and Kubernetes-based workload orchestration.
Experience with Helm charts, Kubernetes ingress, storage, and networking.
Understanding of data center infrastructure, DCIM, or hardware-level monitoring.
Exposure to hybrid cloud or on-premises Kubernetes deployments.
Familiarity with DevSecOps practices and infrastructure security automation.
What We Offer
Opportunity to work on an innovative AI-native Data Center Operating System.
Hands-on exposure to modern cloud, Kubernetes, GPU, and AI infrastructure technologies.
An engineering environment that encourages technical ownership, innovation, and continuous learning.
Opportunities for professional growth as NEXUS expands globally.
Work arrangement
No
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