Senior DevOps Engineer

Accountabilities:: Design, build, and operate Kubernetes and cloud-native infrastructure across AWS, GCP, Azure, and/or OCI, covering compute, storage, networking, and IAM. Own Infrastructure as Code using Terraform, maintaining version-controlled configurations in Git and following consistent engineering practices across environments. Build, maintain, and optimize CI/CD pipelines using Jenkins, Argo CD, Argo Workflows, or comparable GitOps tooling. Automate build, testing, deployment, and release processes across multiple services. Drive release and deployment management practices, including progressive delivery, rollback strategies, and change management designed to reduce operational risk. Configure and harden Apache and Nginx web servers, virtual hosts, and SSL/TLS configurations across environments. Develop and maintain observability capabilities covering metrics, tracing, logging, dashboards, and actionable alerting using technologies such as Prometheus, Grafana, ELK, and Loki. Use AI throughout the delivery lifecycle for scripting, infrastructure development, root-cause analysis, documentation, and runbooks. Establish appropriate guardrails for AI-assisted engineering, including review processes for generated infrastructure code, provenance and licensing checks, and controls around customer and confidential data used in prompts. Manage production networking fundamentals, including TCP/IP, DNS, firewall configuration, and load balancing across cloud and on-premises environments. Participate in on-call rotations and lead or support incident response activities. Conduct post-incident reviews and translate findings into concrete reliability, automation, and operational improvements. Partner with engineering teams to improve deployment velocity, platform reliability, security, and operational efficiency. Modernize legacy infrastructure and continuously identify opportunities to improve cloud-native architecture and engineering practices. Requirements: 5+ years of professional experience in DevOps, Site Reliability Engineering, infrastructure engineering, or a closely related discipline. Deep hands-on experience with Kubernetes, Docker, containerization, and cloud-native architecture patterns. Strong Infrastructure as Code experience using Terraform. Experience with configuration management tools such as Ansible or Puppet. Proven experience building and operating CI/CD pipelines using Jenkins, Argo, GitHub Actions, GitLab CI, or comparable tooling. Strong understanding of GitOps and modern software delivery practices. Solid production networking knowledge, including TCP/IP, DNS, firewall rules, and load balancing across cloud and on-premises environments. Practical experience with observability technologies such as Prometheus, Grafana, ELK, and/or Loki, including the ability to create actionable alerts. Strong Bash and Python scripting capabilities. Experience working with one or more major public cloud platforms, including AWS, GCP, Azure, or OCI. Working knowledge of Linux security fundamentals, including TLS, SSH hardening, patch management, and cloud IAM. Demonstrated experience using AI tools across the software and infrastructure delivery lifecycle, beyond basic code generation. Ability to evaluate which AI models and tools are appropriate for different engineering tasks and recognize situations where AI should not be used. Experience reviewing AI-generated infrastructure code and automation for security, reliability, and operational failure modes. Understanding of AI governance considerations such as code review requirements, provenance, licensing, and restrictions on customer or secret information entering AI prompts. Strong troubleshooting, analytical, communication, and incident-management skills. Ability to work effectively in a fast-paced environment while balancing delivery speed, reliability, and security. Benefits: Full-time opportunity based in Mumbai, India. Flexible work environment with work-from-home, hybrid, or office-based options. Health insurance benefits through established insurance providers. Education and certification sponsorship to support professional development. Flexible leave options to support work-life balance. Learning, mentoring, and career development opportunities across different areas of the business. Inclusive workplace culture with opportunities to participate in employee affinity and community groups. Exposure to large-scale cloud infrastructure, Kubernetes, DevOps automation, observability, and modern AI-assisted engineering practices. Opportunity to work with multiple public cloud platforms and modern infrastructure technologies. Meaningful technical ownership across platform reliability, deployment automation, security, and operational excellence. Additional benefits and employment terms are provided according to the applicable India-based employment package.