devops engineer for voice AI platforms

Krisp develops production products including speech APIs, real-time streaming services, and voice AI platforms.

• Maintain the reliability of core production services end to end, targeting a 99.9% SLA
• Design infrastructure architectures for multi-region, multi-cloud, private cloud, and on-premise enterprise deployments
• Design and build failover mechanisms between regions and cloud providers
• Build monitoring, alerting, and observability tools to detect issues, support incident management, and retain historical monitoring data
• Improve the stability and latency of WebSocket-based real-time streaming services, and optimize network costs and latency across regions
• Deploy new ML models and product features to production with engineering teams
• Lead production incident response, root cause analysis, and post-incident improvements
• Design, implement, and maintain CI/CD pipelines
• Manage system patching and security, and integrate security tools into the infrastructure
• Drive DevOps best practices, standards, and documentation across the team

• 5+ Years of hands-on DevOps experience, including ownership of highly available production systems
• Experience designing and operating systems with strict SLA requirements of 99.9% or higher
• Deep production experience with Kubernetes and containers, including migrations from other orchestration platforms; EKS preferred
• Strong experience with at least one major cloud provider; AWS preferred
• Experience with multi-region and multi-cloud architectures
• Hands-on experience with Terraform and/or Ansible
• Experience designing CI/CD pipelines with Jenkins and GitHub Actions
• Strong experience with Prometheus, Grafana, or similar monitoring and observability stacks, and incident management processes
• Solid networking fundamentals, including TCP/IP, DNS, load balancing, VPNs, firewalls, and CDN
• Strong Linux system administration skills
• Proficiency in bash, Python, or similar scripting languages for automation
• Strong proficiency in Claude Code and AI-assisted coding workflows
• Будет плюсом: private cloud or on-premise enterprise deployments, real-time or low-latency streaming systems (WebSocket, WebRTC, gRPC), production ML model deployment and serving (GPU workloads, inference platforms), cloud network cost optimization

• Условий в вакансии нет