Senior DevOps Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior DevOps Engineer based in India.
This is a senior infrastructure engineering opportunity focused on building and operating reliable, scalable cloud-native platforms. You’ll own critical DevOps capabilities spanning Kubernetes, infrastructure as code, CI/CD, observability, networking, security, and release management. The role combines hands-on engineering with operational ownership, helping development teams deliver quickly while maintaining platform stability and security. You’ll work across major public cloud environments and modernize legacy infrastructure where needed. AI-assisted engineering is an important part of the role, including automation, troubleshooting, infrastructure development, and establishing safe usage practices. You’ll also participate in incident response and use operational insights to drive measurable improvements in reliability.
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.
How Jobgether Works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Work arrangement
No