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Senior Devops/Infrastructure Engineer

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Summary

A senior DevOps/Infrastructure engineer, hybrid in London, who deploys and maintains dev/staging environments, Kubernetes-based ML pipelines and model deployments for carrier-scale Voice AI. Core stack: AWS, Kubernetes, Terraform, Helm/ArgoCD, Prometheus/Grafana, and GPU workloads.

Overview

In this Senior DevOps/Infrastructure role, you will collaborate with Backend and ML/AI engineers to deploy and maintain dev/staging environments and run ML/AI pipelines and model deployments. You’ll design the telco deployment package in partnership with engineers and telco teams, enabling scalable, secure delivery. You will tackle production-grade observability, infrastructure as code, and GitOps practices to support carrier-scale Voice AI initiatives. This is a hybrid London-based opportunity with high ownership and impact on product strategy and execution.

Responsibilities
  • Deploy and maintain dev/staging environments in collaboration with backend and ML/AI teams
  • Design and implement telco deployment package with telco engineering teams
  • Deploy ML models and maintain ML/AI pipelines on Kubernetes
  • Set up and maintain CI/CD and GitOps workflows (Helm, ArgoCD)
  • Implement monitoring and alerting for production systems (Prometheus/Grafana)
  • Manage infrastructure as code and cloud resources (Terraform)
  • Support GPU workloads on Kubernetes (drivers, scheduling, utilization)
  • Ensure secrets management and least-privilege access across environments
  • Experience deploying in air-gapped customer environments
Key requirements
  • Experience with AWS and Kubernetes
  • IaC experience with Terraform
  • GitOps tooling experience (Helm, ArgoCD)
  • Monitoring and alerting setup (Prometheus, Grafana)
  • MLOps in Kubernetes (Kubeflow etc)
  • Running GPU workloads on Kubernetes
  • Familiarity with AI engineering
  • Experience deploying in air-gapped environments
  • Secrets management and least-privilege access across environments
  • Desirable Azure experience
  • Strong collaboration with cross-functional teams
  • ownership and autonomy
  • cross-functional collaboration
  • problem solving and adaptability
  • AWS
  • Kubernetes
  • Terraform

Skills

See also

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