Senior DevOps Platform Engineer- CTI

We're looking for a Senior Platform Engineer to join our CTI Group. We're a startup that builds a lot, so you'll work across a wide range of systems and tools, build new platforms and services, and have real influence over where the platform goes next.You'll work on the platform behind our CTI products: the microservices running on Kubernetes, the cloud and on-prem environments around them, and the infrastructure behind the systems. There's a lot still to build, and you'll have a real say in what comes next.ResponsibilitiesOwn what you build end to end, from design through implementation to running it in production.Design and build the internal platforms, tools, and services other engineering teams rely on, and add new ones as we grow.Make architectural decisions across infrastructure, applications, networking, security, and data.Design, build, and maintain our cloud and on-prem environments.Build and operate the infrastructure behind our AI/ML systems at scale.Manage and evolve our Kubernetes environments.Build and maintain CI/CD pipelines, deployment automation, and Infrastructure-as-Code with Terraform.Build security into the platform, from IAM and secrets management to network policies.Set up the monitoring and observability that show us how the platform is doing.Design for scalability, availability, performance, and resilience in high-scale production systems.Apply Infrastructure-as-Code practices (Terraform) end to end.Requirements: 5 years in DevOps or Platform Engineering roles.Strong software engineering skills, including production-grade Python development using OOP, and proficiency in Bash scripting.Experience designing and building platforms and infrastructure from scratch.A strong architectural sense: you understand how infrastructure, applications, networking, security, and data fit together.Hands-on AWS experience.Solid Kubernetes experience, including deploying, operating, and troubleshooting clusters.Experience with Terraform and Docker, and comfort with Linux, networking, and security fundamentals.Experience with high-scale production systems and with the infrastructure behind AI/ML workloads.A startup mindset: hands-on, curious, and comfortable with broad scope and a lot of room to shape your own work.Bonus Points:Experience in the cyber security field.On-prem, customer private cloud, or air-gapped deployment experience.Model serving and ML tooling such as MLFlow, and GPU scheduling on Kubernetes.Observability stacks such as Prometheus, Grafana, or Loki.This position is open to all candidates.