Lead Cloud & DevOps Engineer; Azure & Kubernetes

Are you passionate about AI?

At Satori Analytics, we aim to change the world one algorithm at a time by bringing clarity to global brands through Data & AI. From cloud-based ecosystems for fintech to predictive models for airlines, our cutting-edge solutions cover the entire data lifecycle—from ingestion to AI applications.

As a fast-growing scale-up, our team of 100+ tech specialists—including Data Engineers, Data Scientists, and more—delivers innovative analytics solutions across industries like FMCG, retail, manufacturing and FSI. Join us as we lead the data revolution in South-Eastern Europe and beyond!

We’re looking for a Senior/Lead Cloud & Dev Ops Engineer who is equally comfortable building infrastructure in the cloud, operating Kubernetes platforms on-premises, and leading a team of Cloud Engineers
. You’ll own the technical direction and day-to-day execution of the Cloud Engineering function while remaining hands‑on with the platforms that power our data, AI, and software solutions.

• Lead the team: Manage, mentor, and grow a team of Cloud Engineers, owning their technical roadmap, priorities, engineering standards, and delivery commitments.
• Plan ahead: Partner with engineering and business leadership on capacity planning, infrastructure priorities, and future team and technology needs.
• Build the platform: Architect and operate cloud and on-premises infrastructure — Azure environments (networking, identity, compute, storage, security) and Kubernetes platforms on both AKS and on-prem — for production apps, data platforms, and AI workloads.
• Automate everything: Drive Infrastructure-as-Code and Git Ops, design CI/CD pipelines, and build reusable, self-service platform capabilities.
• Keep it reliable: Own observability, capacity planning, backup/recovery, HA and DR, and lead the response to complex production incidents across the app, Kubernetes, OS, network, and cloud layers.
• Secure it: Implement security best practices — secrets management, access controls, network segmentation, vulnerability management, and hardening.
• Support AI at scale: Work with Software, Data, and AI Engineers to design infrastructure for data-intensive and GPU/AI workloads, championing Cloud, Dev Ops, Kubernetes, and SRE best practices across engineering.

• 7+ years in Cloud Engineering, Dev Ops, SRE, Platform, or Infrastructure Engineering, including leading, mentoring, and developing technical teams while maintaining a high engineering bar.
• Deep hands‑on experience with Microsoft Azure (networking, compute, storage, identity, security, managed services).
• Strong Kubernetes expertise — designing, deploying, upgrading, securing, and troubleshooting production clusters, including in on-premises or hybrid environments where you own more than the application layer.
• Strong Infrastructure-as-Code with Terraform (Bicep/ARM a plus) and solid Docker / containerized workloads experience (registries, image management, security).
• Experience designing and maintaining CI/CD and Git Ops workflows (Azure Dev Ops, Git Hub Actions, Argo CD, Flux) and building observability with tools like Prometheus, Grafana, Open Telemetry, and Azure Monitor.
• Deep understanding of Linux, networking, DNS, TLS, load balancing, firewalls, storage, and identity, plus cloud/infra security (RBAC, secrets management, certificates, workload identity).
• Strong scripting and automation (Python, Bash, Power Shell, or similar) and a track record designing highly available, resilient, secure, scalable infrastructure.
• Able to balance technical leadership, people management, and hands‑on engineering, with fluent English and strong technical communication and documentation.

• Previous Cloud/Dev Ops/SRE/Platform Team Lead or Engineering Manager experience, or building and scaling a Cloud/Platform Engineering function.
• Designing and operating bare‑metal or private‑cloud Kubernetes clusters, and distributions such as RKE2, Open Shift, Rancher, or Talos.
• GPU infrastructure and Kubernetes GPU workloads (NVIDIA GPU Operator, drivers, scheduling), and supporting AI/ML and data platforms (high‑performance storage, distributed…