June 16, 2026
Platform Engineer
Mid • Hybrid
8,000 - 10,000 PLN
Krakow, Poland
The Intelligent Middleware (IMW) is a suite of critical network services bridging different types of radio networks via a common API. Our technology allows third-party applications to transparently track and communicate with wireless devices, regardless of access network protocols or device types. We connect the unconnected.
Job Description
We are looking for a Platform Engineer to join our growing IMW team in Krakow. In this role, you will play a crucial part in modernizing our virtualization layer, maintaining hybrid infrastructure, and optimizing delivery pipelines to ensure the high reliability of Intelligent Middleware products.
You will be responsible for:
Driving automation of software delivery (CI/CD pipelines) and executing tool migrations to GitHub.
Writing and maintaining Infrastructure as Code (scripts, Ansible) for our on-site lab and hybrid cloud setup.
Development of our virtualization environment on KVM (across Windows and Linux VMs).
Collaborating with dev teams and global IT units to align security, tool utilization, and system scalability.
Leveraging modern AI tools to accelerate coding, scripting, and documentation.
Basic Requirements
2+ years of proven experience in a DevOps, Platform Engineering, or Infrastructure-focused role.
Virtualization & OS: Practical experience or strong understanding of virtualization technologies (ESXi and/or KVM), along with hands-on experience administering both Linux (RedHat) and Windows Server environments.
Infrastructure as Code & Scripting: Strong scripting skills in Python, Bash, or PowerShell, and practical knowledge of Ansible for configuration management.
CI/CD & DevOps Tools: Solid experience with CI/CD tools (specifically Jenkins or GitHub) and pipeline management.
Containerization: Familiarity with Docker and general container orchestration concepts.
Software Development Awareness: Basic understanding of C# / .NET or database concepts (SQL) to effectively collaborate with the development team on architecture simplification.
Additional Assets:
Practical experience with AI coding assistants (e.g., GitHub Copilot, Cursor, Gemini) to speed up refactoring and documentation.
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Warsaw, Poland
🏢 Summary: Principal Platform Engineer to architect and lead the infrastructure strategy for a production-grade ML platform on Google Cloud. The role focuses on building and automating scalable, secure, and resilient infrastructure for high-performance machine learning workloads. You will design cloud-native systems, CI/CD pipelines, and observability solutions to ensure reliable model deployment and operations. 🗂️ Requirements: 8–10+ years in DevOps or Platform Engineering, Minimum 2 years operating production ML workloads, Deep hands-on experience with GCP and GKE, Strong expertise in Kubernetes cluster architecture and operations, Proficiency with Istio service mesh and API gateways, Expert-level Terraform with Atlantis/GitOps workflow, Experience building ML CI/CD pipelines, Experience operating Airflow in production, Experience with ML serving platforms, Experience managing Cloud SQL (PostgreSQL) and BigQuery, Experience with in-cluster datastores, Experience managing enterprise identity and secrets systems 📃 Skills: GCP, GKE, Kubernetes, Istio, Kong, Terraform, Atlantis, GitOps, Helm, Kustomize, ArgoCD, Airflow, Jenkins, GitHub, MLflow, Triton, vLLM, PostgreSQL, BigQuery, Elasticsearch, ClickHouse, Auth0, Dex, ESO, SOPS, IAM, VPC-SC 🏢 Description: Principal Platform Engineer Poland, Remote or Ukraine, Remote or Romania, Remote Point Wild helps customers monitor, manage, and protect against the risks associated with their identities and personal information in a digital world. Backed by WndrCo, Warburg Pincus and General Catalyst, Point Wild is dedicated to creating the world’s most comprehensive portfolio of industry-leading cybersecurity solutions. Our vision is to become THE go-to resource for every cyber protection need individuals may face - today and in the future. Join us for the ride! We’re looking for a Principal Platform Engineer to architect and lead the infrastructure strategy for our next-generation Production ML platform on Google Cloud. In this role, you will be the backbone of our high-performance machine learning workloads, ensuring our systems are elastic, secure, and resilient. You won’t just maintain the status quo; you’ll build the "paved road" for our engineers, automating everything from model deployment to complex networking perimeters. We are a high-trust, outcome-focused team that moves quickly to solve some of the most challenging problems in the ML space. Core Responsibilities: Infrastructure Management: Design, deploy, and maintain elastic scaling cloud infrastructure (GCP) and containerization tools like Kubernetes for high-performance ML workloads. CI/CD Pipeline Development and maintenance: Build automated pipelines for training, testing, and deploying machine learning models using tools like Jenkins, GitHub Actions, or Airflow. Model Monitoring & Maintenance: Implement observability tools to track model drift, accuracy, latency, and performance degradation in production. Collaboration: Bridge the gap between data engineers, ML engineers, Backend and Frontend engineers to ensure smooth production operation. ML Observability: Implement comprehensive monitoring for system health (latency/uptime) alongside ML-specific metrics, such as feature drift, prediction accuracy, and data distribution shifts, to ensure long-term model reliability. Non ML workload and production metrics monitoring. Deploy tools that empower individual teams to monitor their workloads. Participate in on-call rotation, help manage posture to ensure compliance with standards such as SOC. What you bring to the table: Senior Expertise: 8 - 10+ years in DevOps/Platform Engineering, with at least 2 years of experience specifically operating and maintaining production ML workloads . GCP & K8s Mastery: Deep, hands-on experience with GCP (VPC-SC, IAM, Organization Policies) and GKE (Cluster topology, Helm, Kustomize, and in-cluster operators like ArgoCD). Service Mesh Excellence: High proficiency with Istio (VirtualServices, mTLS, sidecar injection) and API Gateways (specifically Kong ). Infrastructure as Code: Expert-level Terraform skills, specifically using an Atlantis/GitOps workflow across a massive, multi-hundred-file estate. Secrets & Identity: Experience managing enterprise-grade identity and secrets (Auth0, Dex, ESO, or SOPS). Data/ML Tooling: Experience operating Airflow in production and an ML-serving stack (e.g., Triton, vLLM, MLflow ). Database Management: Comfortable managing Cloud SQL (PostgreSQL), BigQuery, and in-cluster datastores like Elasticsearch or ClickHouse. At least an upper-intermediate level of spoken and written English. It would be great if you also had: ML Observability: Past experience with continuous monitoring of model accuracy and detecting data/concept drift. Automation Savvy: Experience with Ansible for cluster bootstrap and recovery. Advanced Certifications: Kubernetes (CKA/CKS) or GCP Professional Cloud Architect/Security Engineer certifications. Modern Stack Exposure: Familiarity with Loki, Grafana , or managing ClickHouse at scale. Why Join Us? Professional Growth: Enhance your skills by collaborating closely with talented engineers and architects. Meaningful Impact: Help create software that protects millions of users from cybersecurity threats. Supportive Environment: Join a team dedicated to innovation, mentorship, and continuous learning.