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.
#LI-DHC1
