DevOps Engineer (Vonage AI)

Vonage is a global cloud communications leader that helps businesses accelerate their digital transformation through our fully programmable Unified Communications, Contact Center Applications, and Communications APIs.

Why this role matters;

We're seeking a talented mid-senior level DevOps Engineer to join our AI group, where you will play a crucial role in building and optimizing AI/ML driven services focused on audio, text, and conversational AI. Your work will not only enhance our existing products but also drive cutting-edge innovation, shaping the future of AI-powered solutions within our company.

If you're passionate about scaling AI systems and looking for a role can help to grow your career, we'd love to hear from you!

What will you do?

• Automate business processes to boost engineering productivity and operational excellence.
• Optimize AI/ML performance by working closely with Data Science and Development teams.
• Develop and maintain secure, compliant CI/CD pipelines and incident management tools.
• Collaborate closely with cross-functional teams to integrate security, compliance, and monitoring solutions across engineering workflows.
• Design and implement central observability dashboards assimilating data from various Monitoring, Alert Management and Analytics platforms
• Provide training and support on internal tools to enhance team efficiency.
  
  

What you will bring;

• 4+ Years experience working in a similar mid-Senior level DevOps Engineer role in a larger organization where you are focusing on system design rather than day-to-day operations tasks
• Cloud & Infrastructure – Expert in AWS (EKS, EC2, VPC, IAM, S3, Lambda, API Gateway, etc.), Terraform/Terragrunt, and Infrastructure as Code (Pulumi, Terraform).
• Containerization & Orchestration – Extensive experience with Docker, Kubernetes, Helm, and ArgoCD.
• CI/CD & Automation – Strong expertise in Azure DevOps, GitHub Actions, ArgoCD, and DevOps issue management.
• Monitoring & Security – Experience with logging, monitoring (Grafana, Prometheus, CloudWatch), and a solid understanding of IT security and networking.
• Platform Engineering & AI – Experience building internal platform tools in Python or Go; AI/ML model experience is a plus.
• Collaboration & Integration – Skilled in integrating DevOps tools with Jira, Slack, Confluence, Google Docs, and analytics platforms.
• Self-Driven & Automation-Focused – Works independently with a mindset that everything can be automated.
  
  

Good To Have

• MLops / LLMops experience
• Working on AI/ML projects including building infrastructures, deploying and running self hosted models.