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 an exciting opportunity to join a fast-growing, innovation-driven environment focused on building secure and scalable AI-powered solutions for enterprise use cases. The role offers the chance to design and manage modern cloud infrastructure supporting mission-critical applications and machine learning workloads across multi-cloud environments. Working at the intersection of DevOps, cloud engineering, and AI infrastructure, the successful candidate will play a key role in ensuring reliability, performance, and operational excellence. This position is ideal for professionals who thrive in fast-paced settings and enjoy solving complex infrastructure challenges. You will collaborate closely with engineering, security, and machine learning teams to build resilient systems that support cutting-edge technologies. The role combines hands-on technical ownership with the opportunity to shape infrastructure strategy in a rapidly evolving environment.

• Design, build, and maintain scalable cloud infrastructure across AWS, Google Cloud Platform, and Azure environments.
• Develop and optimize CI/CD pipelines to enable efficient code integration, testing, and automated deployments.
• Implement Infrastructure as Code practices using tools such as Terraform to ensure consistency, repeatability, and scalability.
• Containerize applications and manage orchestration platforms using Docker and Kubernetes.
• Build and operate monitoring, logging, observability, and alerting frameworks to ensure high availability and proactive issue resolution.
• Manage secure, private, and VPC-isolated enterprise deployments with strong emphasis on security, compliance, and audit readiness.
• Collaborate with machine learning teams to deploy and scale AI training and inference workloads, including GPU-enabled infrastructure when required.
• Partner with engineering and security stakeholders to improve infrastructure resilience, operational processes, and cloud cost efficiency.
• Maintain technical documentation and establish best practices for infrastructure operations and platform management.

Requirements

• Minimum of 3 years of experience in DevOps, Cloud Infrastructure, Site Reliability Engineering, or related disciplines.
• Strong hands-on expertise with at least one major cloud platform, including AWS, GCP, and/or Microsoft Azure.
• Solid experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Proven ability to design and manage CI/CD pipelines using GitHub Actions or similar automation tools.
• Practical experience with Infrastructure as Code frameworks, particularly Terraform.
• Strong understanding of networking concepts, including VPCs, cloud security groups, and cloud-native services.
• Experience managing production-grade environments with a focus on scalability, reliability, security, and performance optimization.
• Knowledge of monitoring, logging, and observability platforms and best practices.
• Familiarity with GPU infrastructure and machine learning workload deployment is considered a strong advantage.
• Excellent troubleshooting, analytical thinking, and problem-solving capabilities.
• Strong communication skills in English, with the ability to collaborate effectively across distributed teams.

Benefits

• Fully remote opportunity offering flexibility and work-life balance.
• Opportunity to work on cutting-edge AI and enterprise technology solutions.
• Exposure to multi-cloud architectures and advanced DevOps practices.
• Collaborative and high-growth environment with significant ownership and autonomy.
• Opportunity to work closely with engineering, security, and AI teams on impactful projects.
• Fast-paced startup culture that encourages innovation, continuous learning, and professional development.
• Participation in building scalable infrastructure supporting next-generation AI applications.
• Structured interview process with direct exposure to technical and leadership stakeholders.