About Centific
Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem—comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets—to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.
Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.
About Job
Job Description: DevOps Engineer
Overview
We are seeking a highly skilled DevOps Engineer with some experience in on-premises infrastructure. This role involves deploying, managing, and optimizing on-prem enterprise systems while ensuring network health, resiliency, and service availability through proactive monitoring and incident response.
Key Responsibilities
Deploy and Manage On-Premise Systems
Install, configure, and maintain on-premises servers, containers, and related enterprise applications.
Automate deployment pipelines for infrastructure and applications using industry-standard tools (e.g., Ansible, Chef, Puppet, Jenkins).
Ensure high availability, security, and scalability of on-premises environments.
Cluster and Infrastructure Support
Operate and maintain Kubernetes or similar container orchestration systems in an on-prem environment.
Integrate with existing storage, network, and virtualization platforms.
Manage upgrades, backups, and recovery plans for critical infrastructure.
Automation and Scripting
Develop and maintain scripts for automation of monitoring, configuration management, and operational tasks.
Identify opportunities for operational improvements and implement automation to reduce manual intervention.
Collaboration and Communication
Work closely with application, network, and security teams to align DevOps initiatives with business needs.
Document system configurations and operational processes.
Communicate incident impacts and recovery efforts to stakeholders.
Desired Skills & Experience
Bachelor's degree in computer science, Information Technology, or related field (or equivalent experience).
5+ years in DevOps, Systems Engineering, or related technical roles.
Hands-on expertise in on-prem enterprise infrastructure, including deployment, monitoring, and troubleshooting.
Proficiency with automation/configuration tools (e.g., Ansible, Chef, Puppet), CI/CD tools (e.g., Jenkins, GitLab CI), and container platforms (e.g., Kubernetes).
Strong scripting skills (e.g., Bash, Python, PowerShell).
Familiar with monitoring stacks (Prometheus, Nagios, Grafana, Zabbix) and log management tools (ELK stack, Splunk).
Working knowledge of network concepts (TCP/IP, DNS, load balancing) and security best practices.
Experience with backup and disaster recovery procedures.
Ability to work in a 24x7 support environment and participate in on-call rotations.
Top Skills
What We Do
Zero distance innovation for GenAI creators and industries
Expertly engineering platforms and curating multimodal, multilingual data, we empower the ‘Magnificent Seven’ and enterprise clients with safe, scalable AI deployment
We a team of over 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers.
We bring platforms, partners and 1.8 million vertical domain experts to create high-quality pre-trained datasets, fine-tuned industry-specific LLMs, and RAG pipelines supported by vector databases.
These innovations can reduce GenAI costs by up to 80% and bring GenAI solutions to market 50% faster in 230 locales.
