DevOps Engineer AI Services

🏢 Summary: The offer is for a Senior Platform Engineer responsible for designing, building, and operating scalable Kubernetes-based platforms on AWS. The role focuses on backend platform development, Infrastructure as Code with Terraform, CI/CD automation, and improving developer experience through self-service and multi-tenant solutions. It involves driving reliability, observability, and automation across a cloud-native ecosystem. 🗂️ Requirements: 5+ years of experience as a Platform Engineer, Strong hands-on experience with Kubernetes, including cluster operations, Strong programming skills in TypeScript or Go, Experience with AWS or other cloud platforms, Experience with Infrastructure as Code tools, preferably Terraform, Experience with CI/CD pipelines and deployment automation, Experience designing scalable multi-tenant systems, Strong understanding of API and platform architecture, Solid Linux and networking fundamentals, Experience with observability and monitoring solutions, Experience building self-service platform capabilities, Practical experience using AI-powered coding assistants, Work permit and residence in the European Union 📃 Skills: Kubernetes, AWS, Terraform, TypeScript, Go, Python, CI/CD, Linux, Networking, APIs, Docker, OpenTelemetry, Backstage, GitHub, Claude, Cursor 🏢 Description: 🟣 You will be: designing, building, and operating scalable Kubernetes-based platform infrastructure, developing backend platform services and reusable engineering components, building and maintaining cloud-native solutions (primarily on AWS), creating and evolving Infrastructure as Code solutions using Terraform, designing and implementing CI/CD pipelines and deployment automation, developing scalable multi-tenant platform capabilities for engineering teams, building self-service developer platform features and internal tooling, designing and maintaining APIs and platform architecture standards, improving platform reliability, observability, and monitoring capabilities, collaborating with engineering teams to improve developer experience and platform adoption, contributing to platform engineering best practices and technical standards, supporting container platform operations and orchestration processes, driving automation and operational excellence across the platform ecosystem. 🟣 Your profile: 5+ years of experience as a Platform Engineer, practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery, strong hands-on experience with Kubernetes, including cluster operations and orchestration concepts, strong backend engineering background, strong programming skills in TypeScript and/or Go; Python experience is a plus, solid experience with cloud platforms, preferably AWS, practical experience with Infrastructure as Code tools, preferably Terraform, experience with CI/CD pipelines and deployment orchestration, experience designing scalable multi-tenant systems, strong understanding of API and platform architecture, solid Linux and networking fundamentals, experience with observability and monitoring solutions, experience building reusable self-service platform capabilities for developers, good English communication skills (at least B2 level). 🟣 Nice to have: experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work, interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches, experience with Internal Developer Platforms (IDP), experience building Kubernetes operators and controllers, experience with Backstage or developer portal tooling, experience in container runtime or platform engineering, knowledge of event-driven and distributed systems architecture, experience with service mesh technologies and OpenTelemetry. Work from the European Union region and a work permit are required. 🟣 Recruitment Process: CV review – HR Call – Interview – Client Interview – Decision 🎁 Benefits 🎁 ✍ Development: development budget of up to 6,800 PLN, we fund certifications e.g.: AWS, Azure, ISTQB, PSM, access to Udemy, Safari Books Online and more, events and technology conferences, technology Guilds, internal training, Xebia Library, Xebia Upskill. 🩺 We take care of your health: private medical healthcare, multiSport card - we subsidise a MultiSport card, mental Health Support. 🤸‍♂️ We are flexible: flexible working hours, B2B or permanent contract, contract for an indefinite period.

🏢 Summary: On-site role in Wroclaw for a Kubernetes & Cloud Infrastructure Engineer focused on building and operating scalable, secure AI platform infrastructure. The position centers on managing Kubernetes clusters, AWS environments, and infrastructure as code to support GPU workloads and large language model deployments. You will enhance reliability, automation, and observability of cloud-native AI systems. 🗂️ Requirements: 4+ years in Cloud, DevOps, or Platform Engineering, Strong expertise in Kubernetes cluster operations and multi-tenancy, Experience with GPU scheduling and model serving infrastructure, Hands-on experience with AWS (networking, IAM, EKS, EC2), Proficiency in Python, Experience with Terraform and infrastructure as code, Ability to build and operate CI/CD pipelines, Experience implementing GitOps workflows, Experience defining and managing infrastructure SLOs, Fluent English, Legal right to work in the EU 📃 Skills: Kubernetes, AWS, EKS, EC2, IAM, Terraform, Helm, Kustomize, Python, CI/CD, GitOps, GPU, Docker, Linux, Networking, Observability 🏢 Description: Unleash the power of cloud-native infrastructure — revolutionize AI platforms with your expertise! Wroclaw-based opportunity with on-site work model As a Kubernetes & Cloud Infrastructure Engineer – AI Platform , you will be working for our client, a leader in AI innovation, building and managing critical infrastructure that supports advanced AI models and large language model workloads. Your work will directly impact the delivery, scalability, and security of cutting-edge AI solutions, empowering teams across the firm to harness AI's full potential. Join us and be part of shaping the future of intelligent technologies! Your main responsibilities: Build and operate scalable Kubernetes clusters supporting multi-tenancy, GPU workloads, and model serving. Manage AWS infrastructure, including networking, IAM, security, and cost optimization. Develop and maintain infrastructure as code utilizing tools like Terraform, Helm, and Kustomize. Implement and maintain CI/CD and GitOps workflows to streamline deployment pipelines. Build observability solutions for system health, utilization, latency, and platform performance monitoring. Automate scaling, capacity management, and enforce security and governance policies across cloud and on-premise environments. Define and monitor infrastructure Service Level Objectives (SLOs) to ensure reliability and performance. Collaborate closely with AI Platform Engineers, Data Scientists, and Research teams to support model inference and deployment infrastructure. Enable internal teams through platform tooling, onboarding, and self-service portals. You're ideal for this role if you have: 4+ years of experience in Cloud, DevOps, or Platform Engineering. Strong expertise in Kubernetes, including cluster operations, multi-tenancy, GPU scheduling, and Helm/Kustomize. Hands-on experience with AWS cloud services—networking, IAM, EKS, EC2, and cost management. Proficient in Python and infrastructure-as-code tools such as Terraform. Proven ability to build and operate CI/CD and GitOps workflows. Skilled in defining and managing infrastructure SLOs. Pragmatic, ownership-driven approach and comfortable working in ambiguous environments. It is a strong plus if you have: Experience supporting LLM inference workloads, model serving platforms, or GPU-backed infrastructure. Knowledge of RAG systems, vector databases, or AI-related data platforms. Background in high-performance or latency-sensitive environments. Relevant certifications such as CKA, CKAD, Solutions Architect, or similar. Language Required for the role: Fluent English Eligibility to work in this role: Only candidates with an existing legal right to work in the European Union will be considered for this role. #MAKEYourCareerBETTER Interested? Apply now and include your CV (preferably in English) along with a statement confirming your consent to the processing and storage of your personal data.

🏢 Summary: The role involves designing, building, and operating scalable and secure Azure Kubernetes Service (AKS) platforms with a strong focus on cloud-native technologies, automation, and GitOps. The engineer will manage containerized workloads, implement autoscaling and observability solutions, and define infrastructure as code in production Azure environments. This position emphasizes platform security, CI/CD, and support for advanced workloads including GPU-based deployments. 🗂️ Requirements: Strong hands-on experience with Kubernetes in production environments, Experience with Azure Kubernetes Service (AKS), Advanced knowledge of Docker and containerization, Experience implementing autoscaling with KEDA, Proficiency in Helm, Experience with Azure services (AKS, ACR, Key Vault, Managed Identities, Azure Monitor), Experience building CI/CD pipelines, Experience implementing GitOps workflows (Flux or Argo CD), Experience with Infrastructure as Code (Terraform, Bicep, or ARM), Experience with observability tools (Prometheus, Grafana, OpenTelemetry), Strong scripting skills (Bash or Python), Understanding of Kubernetes security best practices 📃 Skills: Kubernetes, AKS, Docker, KEDA, Helm, Azure, ACR, KeyVault, ManagedIdentities, AzureMonitor, AzureDevOps, GitLab, Flux, ArgoCD, Terraform, Bicep, ARM, Prometheus, Grafana, OpenTelemetry, Bash, Python, PowerShell, GitOps, RBAC, NVIDIA, GPU 🏢 Description: Azure Kubernetes Platform Engineer We are seeking a skilled Azure Kubernetes Platform Engineer to design, build, and operate scalable, secure, and high-performance Kubernetes platforms on Azure. This role is ideal for someone passionate about cloud-native technologies, platform engineering, and enabling teams through robust infrastructure and automation. Key Responsibilities Design, deploy, and manage production-grade platforms on Azure Kubernetes Service (AKS). Build and optimize containerized workloads using Docker, ensuring efficiency and security. Implement event-driven autoscaling solutions using KEDA. Develop and maintain reusable Helm charts to support scalable application deployments. Manage and integrate Azure services such as ACR, Key Vault, Managed Identities, and Azure Monitor. Build and maintain CI/CD pipelines using Azure DevOps or GitLab CI, with a strong focus on GitOps practices (Flux or Argo CD). Support GPU-based workloads, including configuration of NVIDIA device plugins and GPU node pools. Implement robust observability solutions using Prometheus, Grafana, and OpenTelemetry. Ensure platform security through Kubernetes best practices, including RBAC, workload identity, and non-root containers. Define and manage infrastructure using Terraform, Bicep, or ARM templates. Core Skills & Experience Strong hands-on experience with Kubernetes, particularly Azure Kubernetes Service (AKS), in production environments. Advanced knowledge of containerization and Docker best practices. Experience implementing autoscaling using KEDA (ScaledObjects and ScaledJobs). Proficiency in Helm for packaging and deploying applications. Solid experience across the Azure ecosystem (AKS, ACR, Key Vault, Managed Identities, Azure Monitor). Experience building CI/CD pipelines and implementing GitOps workflows. Familiarity with GPU workloads in Kubernetes environments. Strong scripting skills in Bash and Python (PowerShell beneficial). Experience with observability and monitoring tools (Prometheus, Grafana, OpenTelemetry). Understanding of Kubernetes security and Infrastructure as Code principles. Nice to Have Advanced KEDA scaling patterns (e.g., Azure Service Bus, Prometheus metrics, cron-based scaling). Experience with Python-based machine learning workloads and modern packaging tools (uv, pyproject.toml, tox). Knowledge of PostgreSQL and Redis in highly available containerized environments. Experience with Java / Spring Boot microservices. Familiarity with workflow orchestration tools such as Temporal, Ray, or Argo Workflows. Exposure to WASM/WASI workloads on Kubernetes. FinOps experience in multi-team Kubernetes environments. Relevant certifications (e.g., CKA, CKAD, CKS, AZ-104, AZ-400, AZ-305). Why Join Us? Work on cutting-edge cloud-native and Kubernetes technologies. Build platforms that empower engineering teams at scale. Collaborate in a highly technical, forward-thinking environment.

🏢 Summary: Engineering role focused on building a unified infrastructure platform that bridges bare-metal servers, GPU clusters, storage, and networking into a programmable system for large-scale AI and HPC workloads. The position involves designing orchestration layers, automation frameworks, APIs, and observability systems to manage compute, storage, and networking at scale. The goal is to deliver high-performance, compliant, and enterprise-grade AI infrastructure for demanding research and production environments. 🗂️ Requirements: 5+ years software engineering experience in infrastructure platforms, distributed systems, or cloud platforms, Strong Kubernetes knowledge and container orchestration experience, Deep understanding of compute, storage, and networking infrastructure, Experience with systems programming languages (Go, C/C++, Rust, Python), Strong Linux production experience, Knowledge of bare-metal provisioning and virtualization technologies, Experience designing APIs, SDKs, and automation frameworks, Familiarity with AWS, GCP, or Azure, Experience with Infrastructure-as-Code tools, Experience with network automation and high-performance networking concepts, Understanding of observability, telemetry, and logging systems, Knowledge of enterprise security and compliance standards (SOC2, ISO27001) 📃 Skills: Go, Python, Kubernetes, Docker, Terraform, Ansible, Linux, KVM, SLURM, AWS, GCP, Azure, BGP, VXLAN, InfiniBand, RDMA, SR-IOV, FastAPI, PostgreSQL, Redis, Prometheus, Grafana, ELK, NVIDIA 🏢 Description: Moonlite delivers high-performance AI infrastructure for organizations running intensive computational research, large-scale model training, and demanding data processing workloads.We provide infrastructure deployed in our facilities or co-located in yours, delivering flexible on-demand or reserved compute that feels like an extension of your existing data center. Our team of AI infrastructure specialists combines bare-metal performance with cloud-native operational simplicity, enabling research teams and enterprises to deploy demanding AI workloads with enterprise-grade reliability and compliance. Your Role: You will be foundational to building the comprehensive infrastructure platform that bridges our physical infrastructure – bare-metal servers, GPU clusters, high-performance storage, and networking fabric – with the systems our customers depend on for large-scale computation, inference, simulations, and training. Working closely with product, your platform team members, and infrastructure specialists, you'll design and implement the orchestration layer, APIs, and automation framework that make thousands of servers, petabytes of storage, and high-speed networks feel like a unified, programmable platform. Job Responsibilities Infrastructure Abstraction Layer: Design and build systems that bridge physical infrastructure (bare-metal servers, storage clusters, network fabric) with customer-facing services, enabling programmatic management of compute, networking, and storage at scale. Research Cluster Provisioning: Design and implement systems for provisioning and managing research computing environments including Kubernetes and SLURM clusters, enabling automated deployment, resource scheduling, and workload orchestration for distributed AI training and HPC workloads. Platform Orchestration: Implement comprehensive orchestration systems that coordinate across compute, storage and networking to deliver unified experience for complex research workloads. Network Automation & Placement: Design and build network provisioning automation including intelligent VM placement decisions for optimal network topology, automated VLAN and subnet configuration, and software-designed networking orchestration for high-performance interconnects. Enterprise APIs & SDKs: Develop robust APIs and SDKs that enable researchers and engineering teams to programmatically provision and manage infrastructure resources across all platform domains. Observability & Telemetry: Implement comprehensive observability, telemetry, and logging systems that provide visibility into infrastructure health, performance, and utilization across the infrastructure footprint. Performance Engineering: Build and optimize platform services that deliver consistent high-throughput low-latency networking for demand research applications and data-intensive workloads. Cross-Team Collaboration: Work closely with engineering, infrastructure, and product to define requirements, drive infrastructure-product-rollouts, and improve resource lifecycle management. Compliance & Security: Implement platform-wide compliance and security features supporting SOC 2, ISO 27001, and enterprise regulatory requirements including comprehensive audit logging, access controls, and data residency management. Requirements Experience: 5+ years in software engineering with a proven track record of infrastructure platforms, distributed systems, or cloud platforms for production environments. Kubernetes & Container Orchestration: Strong familiarity with Kubernetes architecture, container orchestration concepts, and experience deploying workloads in Kubernetes environments. Understanding of pods, deployments, services, and basic Kubernetes operations. Infrastructure Systems: Strong understanding of infrastructure fundamentals including compute orchestration, storage systems, networking technologies, and how they integrate together to deliver complete platform experiences. Programming Skills: Experience with systems programming languages (Go, C/C++, Rust, Python) for performance-critical components is a strong plus. Linux Production Experience: Strong experience with linux in production environments, including systems administration, performance tuning, and troubleshooting. Bare-Metal & Virtualization: Deep knowledge of bare-metal infrastructure, provisioning systems, out-of-band management, and virtualization technologies (KVM, Kubernetes, etc). API & Platform Design: Proven experience designing and building APIs, SDKs, and automation frameworks that enable programmatic infrastructure management. Cloud Platform Knowledge: Strong familiarity with cloud environments (AWS, GCP, Azure) and understanding of how to translate cloud-native patterns to bare-metal infrastructure. Infrastructure Automation: Experience with Infrastructure-as-code tools (Terraform, Ansible) and building automated deployment pipelines. Problem Solving & Autonomy: Self-starter who can navigate ambiguity, balance pragmatic shipping with good long-term architecture, and independently drive complex technical initiatives. Communication Skills: Strong written and verbal communication skills, including ability to write clear technical communication and collaborate across teams. Commitment to Growth: Growth mindset with continuous focus on learning and professional development. Preferred Qualifications Background provisioning or managing research computing environments (Kubernetes, SLURM, or HPC clusters) Experience building internal platforms, infrastructure-as-a-service, or developer tooling Background with GPU computing platforms and AI/ML infrastructure requirements Knowledge of high-performance networking technologies (InfiniBand, RDMA, SR-IOV) Experience with observability and monitoring platforms (Prometheus, Grafana, ELK stack) Familiarity with both cloud-native and bare-metal infrastructure deployment models Understanding of enterprise compliance requirements and security best practices Extra points for experience with financial services technology infrastructure and understanding of trading system requirements Key Technologies Go, Python, Kubernetes, Docker, Terraform, Ansible, Linux, Networking (BGP, VXLAN), Storage Systems, FastAPI, PostgreSQL, Redis, NVIDIA GPU Technologies, InfiniBand Why Moonlite Build Next-Generation Infrastructure: Your work will create the platform foundation that enables financial institutions to harness AI capabilities previously impossible with traditional infrastructure. Hands-On Ownership: As an early engineer, you'll have end-to-end ownership of projects and the autonomy to influence our product and technology direction. Shape Industry Standards: Contribute to defining how enterprise AI infrastructure should work for the most demanding regulated environments. Collaborate with Experts: Work alongside seasoned engineers and industry professionals passionate about high-performance computing, innovation, and problem-solving. Start-Up Agility with Industry Impact: Enjoy the dynamic, fast-paced environment of a startup while making an immediate impact in an evolving and critical technology space. We offer a competitive total compensation package combining a competitive base salary, startup equity, and industry-leading benefits. The total compensation range for this role is $165,000 – $225,000, which includes both base salary and equity. Actual compensation will be determined based on experience, skills, and market alignment. We provide generous benefits, including a 6% 401(k) match, fully covered health insurance premiums, and other comprehensive offerings to support your well-being and success as we grow together. #li-remote

🏢 Summary: Platform Engineer / DevOps role focused on building and standardizing multi-cloud Kubernetes environments using Infrastructure-as-Code. The position centers on Terraform-driven provisioning across AWS, Azure, and GCP, GitOps-based deployment automation, and enterprise-grade security and identity integration. The engineer supports internal and client environments, ensuring portable, secure, and reliable cloud-native deployments. 🗂️ Requirements: Strong Terraform experience across AWS Azure and GCP, Hands-on experience with EKS AKS and GKE, Practical knowledge of Kubernetes networking node pools workload identity private clusters ingress storage classes cluster upgrades, Experience with GitOps workflows and Helm release management, Experience with GitHub Actions and OIDC authentication, Experience with Terraform remote state management, Ability to deploy into secure enterprise environments with strict security audit and change-control requirements, Experience debugging Kubernetes CRDs RBAC networking DNS ingress and identity issues, Fluent English, EU residency and valid EU work authorization 📃 Skills: Terraform, Kubernetes, AWS, Azure, GCP, EKS, AKS, GKE, Helm, GitOps, GitHubActions, OIDC, OCI, AzureOpenAI, ACR, KeyVault, Postgres, Databricks, OpenTelemetry, RBAC, DNS, Ingress 🏢 Description: Join Our Team as a Platform Engineer / DevOps - Multi-Cloud IaC Are you a hands-on Infrastructure-as-Code expert who can provision real Kubernetes environments across AWS, Azure, and GCP, while keeping security, auditability, portability, and operational reliability in mind? PortBlueSky is supporting a major multinational enterprise in scaling a widely adopted open-source, Kubernetes-native agentic AI platform. We are looking for a Platform Engineer / DevOps specialist to provision internal environments and support multi-cloud client deployments, with a strong focus on Terraform, Kubernetes, GitOps, and cloud-native identity. This role is ideal for someone who can move between cloud infrastructure, CI/CD, Kubernetes debugging, deployment automation, and client advisory work. Role and Responsibilities As Platform Engineer / DevOps, you will: Provision internal and client environments: Build and maintain repeatable Kubernetes deployment environments across AWS, Azure, and GCP. Own multi-cloud IaC patterns: Use Terraform to define secure, maintainable, portable infrastructure for EKS, AKS, GKE, networking, storage, identity, and deployment dependencies. Build Azure parity: Help establish strong Azure deployment patterns, including AKS, Azure managed identity, Azure OpenAI, Azure networking, Azure Container Registry, Key Vault, Terraform, and GitHub Actions. Support enterprise deployment requirements: Work within client infrastructure constraints, including strict security, audit, change-control, network, registry, and identity requirements. Standardize deployment automation: Improve GitOps workflows, Helm release management, OCI chart/image handling, GitHub Actions/OIDC, Terraform remote state, environment promotion, and cluster bootstrap automation. Integrate with client stacks: Support deployment patterns for Databricks, S3-compatible storage, managed Postgres, OTEL, model gateways, private registries, and cloud-native secret systems. Debug practical failures: Resolve issues around CRDs not being established, unavailable APIService resources, webhook certificates, image pulls, RBAC denials, network policies, DNS, ingress, and cloud identity. Support forward-deployed engineering: Help client teams that lack internal Kubernetes, DevOps, or cloud-platform maturity adopt robust deployment patterns. What We Offer A technically challenging platform mission: Work on a real open-source platform being scaled for enterprise adoption across cloud providers and client-owned environments. A senior, developer-led culture: PortBlueSky publicly positions itself around top 1% technical experts, senior engineering talent, and challenging projects for leading corporations. Remote-first flexibility: Work in a remote-first setup with flexible conditions and a strong work-life balance. High ownership: Shape how environments are provisioned, promoted, secured, upgraded, and supported. Practical impact: Your work will directly affect whether the platform can be adopted by enterprise teams with confidence. About You You are an experienced Platform Engineer, DevOps Engineer, or Cloud Infrastructure Engineer with: Strong Terraform experience across AWS, Azure, and GCP. Hands-on experience with EKS, AKS, and GKE. Practical knowledge of Kubernetes networking, node pools, workload identity, private clusters, managed ingress, storage classes, and cluster upgrade workflows. Experience with GitOps, Helm release management, OCI charts/images, GitHub Actions/OIDC, Terraform remote state, and environment promotion. Experience deploying into client infrastructure or multi-cloud environments with security, audit, and change-control requirements. A preference for portable, vendor-agnostic patterns while still using native cloud identity and infrastructure where appropriate. Strong debugging skills and calmness under deployment pressure. Fluent English and comfort working in a distributed, international team. EU residency and permission to work in the EU. Nice to Have Deep Azure experience, especially AKS, managed identity, Azure OpenAI, Azure Container Registry, Key Vault, and private networking. Experience with Databricks, managed Postgres, OTEL, model gateways, private registries, or enterprise secrets management. Familiarity with agentic AI platforms, Kubernetes-native control planes, MCP/A2A flows, or workflow orchestration. Experience supporting enterprise clients in consulting, staff augmentation, or forward-deployed roles. Technologies & Tools You May Work With Terraform AWS / EKS Azure / AKS GCP / GKE Kubernetes Helm GitHub Actions / OIDC GitOps OCI registries Azure OpenAI Azure Container Registry Azure Key Vault Managed Postgres Databricks OpenTelemetry Private registries Cloud-native identity systems Ready to build the multi-cloud foundations for a serious enterprise AI platform? Apply now and help create deployment patterns that work across real-world client environments. Apply Now!

🏢 Summary: Backend engineering role focused on building scalable Python services and APIs for an AI platform used by enterprise customers. The position involves developing production backend systems, integrating AI components, and improving reliability in a collaborative engineering environment. Offers modern AI tooling, cloud-native development exposure, and growth opportunities within an AI-focused product team. 🗂️ Requirements: 2–5 years of backend application development experience, Python, REST APIs, Backend services, SQL, PostgreSQL, Asynchronous programming, Background job processing, AWS, Azure, GCP, Testing, Version control, AI development tools, English B2 📃 Skills: Python, FastAPI, Django, PostgreSQL, SQL, AWS, Azure, GCP, Docker, Redis, RabbitMQ, Kafka, TypeScript, REST, Git, CI/CD, ChatGPT, Copilot, Codex, Claude 🏢 Description: About Us Many companies want to use AI agents, but these agents often struggle with real business tasks. We solve this problem by building a platform that helps AI understand business rules, workflows, and processes. This enables AI to make better decisions and provide accurate, reliable, and trustworthy results. Our technology is used by leading companies across multiple industries to automate up to 85% of customer cases, reduce handling time by 20–25%, and complete tasks that previously took hours in just seconds. We work with leading technology partners and have been recognized for our innovative approach. Our mission is to help people everywhere get better answers through AI. About the Role We are looking for a Mid Backend Engineer to help build scalable backend services that power our AI platform. You'll work closely with experienced backend engineers, frontend developers, product managers, and platform engineers to develop new features, improve existing systems, and deliver reliable production software. This is a great opportunity to work on modern AI infrastructure while growing your technical skills in a collaborative engineering environment. Responsibilities - Build and maintain backend services, APIs, and background processing systems. - Develop scalable application logic using Python. - Collaborate with product managers and engineers to deliver new product features. - Integrate backend services with databases, external APIs, and AI components. - Monitor, troubleshoot, and improve production services. - Write clean, maintainable, and well-tested code. - Participate in code reviews and engineering discussions. - Improve development workflows using AI tools and automation. - Continuously learn from production feedback and contribute to improving system reliability and performance. Requirements - 2–5 years of experience building production backend applications. - Good knowledge of Python. - Experience building REST APIs and backend services. - Understanding of relational databases (PostgreSQL or similar) and SQL. - Familiarity with asynchronous programming and background job processing. - Basic understanding of cloud platforms such as AWS, Azure, or GCP. - Understanding of software engineering best practices, testing, and version control. - Good communication skills and willingness to collaborate across engineering and product teams. - Experience using AI development tools such as GitHub Copilot, Claude Code, ChatGPT, or similar. - English at B2 level or higher. Nice to Have - Experience with FastAPI, Django, or similar Python frameworks. - Experience working with Docker and CI/CD pipelines. - Familiarity with Redis, RabbitMQ, Kafka, or similar messaging technologies. - Experience building AI-powered applications or integrating LLM APIs. - Basic knowledge of TypeScript or frontend development. - Interest in distributed systems and cloud-native architectures. What We Offer - 20,000–24,000 PLN B2B (depending on experience). - Company stock options. - MacBook Pro. - Modern technology stack with opportunities to contribute to open-source projects. - Access to advanced AI development tools, including GitHub Copilot, Claude Code, OpenAI Codex, TypingMind, and MCP Servers. - The opportunity to work on production AI systems used by enterprise customers. - A collaborative engineering culture focused on learning, ownership, and continuous improvement. - Career growth alongside experienced engineers in a fast-growing AI company. Our Culture and Values - Quality - We build reliable software with attention to detail and long-term maintainability. - Momentum - We move quickly, learn continuously, and improve through iteration. - Accountability - We take responsibility for our work and communicate openly. - Hard Work - We solve ambitious problems together and support each other along the way. - Learning Agility - We stay curious, embrace feedback, and continuously develop our skills. - Adapt and Thrive - We welcome change and see challenges as opportunities to improve. - Win Together - We collaborate, share knowledge, and succeed as one team.

🏢 Summary: Role for an experienced Kubernetes / Platform Engineer responsible for designing, implementing and developing modern container platforms in on-premise and hybrid environments. The position focuses on building and integrating Kubernetes clusters with data center infrastructure, automating processes, and supporting production environments. Opportunity to work on advanced infrastructure projects with real impact on architecture and technology choices. 🗂️ Requirements: Minimum 3 years of experience with Kubernetes, DevOps or Linux, Experience in at least 2 Kubernetes or container platform implementation projects, Strong knowledge of Kubernetes architecture, components and CNI networking, Good knowledge of Linux systems (RHEL, Ubuntu or Rocky), Knowledge of data center infrastructure: networking (L2/L3, load balancing), storage, compute, virtualization, HA, Experience with automation tools such as Terraform or Ansible, Ability to design architecture and analyze technical problems, English proficiency for working with technical documentation 📃 Skills: Kubernetes, RKE2, OpenShift, Rancher, OKD, Linux, RHEL, Ubuntu, Rocky, Terraform, Ansible, GitOps, ArgoCD, Flux, Ceph, Networking, CNI, L2, L3, HA, Virtualization, CICD, Storage, Compute 🏢 Description: Poszukujemy doświadczonego Kubernetes / Platform Engineera , który będzie odpowiedzialny za projektowanie, wdrażanie oraz rozwój nowoczesnych platform kontenerowych w środowiskach on-premise i hybrydowych. To rola dla osoby, która chce pracować z zaawansowaną infrastrukturą, projektować architekturę rozwiązań i mieć realny wpływ na środowiska produkcyjne klientów. 🔧 Zakres obowiązków Projektowanie, wdrażanie i rozwój platform Kubernetes (on-prem / hybrid) Budowa i konfiguracja klastrów (upstream Kubernetes, RKE2, OpenShift, Rancher) Integracja Kubernetes z infrastrukturą data center (compute, network, storage) Analiza wymagań klientów oraz dobór architektury rozwiązania Automatyzacja procesów (Infrastructure as Code, GitOps) Diagnostyka, optymalizacja i utrzymanie środowisk produkcyjnych Testowanie i walidacja nowych technologii Wsparcie klientów w utrzymaniu i rozwoju platform Współpraca z zespołami projektowymi oraz udział w działaniach pre-sales Wymagania Min. 3 lata doświadczenia w obszarze Kubernetes / DevOps / Linux Udział w co najmniej 2 projektach wdrożeniowych (Kubernetes / platformy kontenerowe) Bardzo dobra znajomość Kubernetes (architektura, komponenty, networking – CNI) Dobra znajomość systemów Linux (RHEL / Ubuntu / Rocky Linux) Wiedza z zakresu infrastruktury data center: networking (L2/L3, load balancing) storage (block / file / object, np. Ceph) compute / wirtualizacja / HA Doświadczenie z narzędziami automatyzacji (Terraform, Ansible lub podobne) Umiejętność analizy problemów i pracy projektowej Znajomość języka angielskiego (praca z dokumentacją techniczną) Mile widziane Certyfikacje Kubernetes (CKA / CKAD / CKS) Doświadczenie z OpenShift, Rancher, OKD Znajomość GitOps (ArgoCD, Flux) Doświadczenie z systemami storage (np. Ceph) Znajomość narzędzi CI/CD Oferujemy Pracę przy zaawansowanych projektach infrastrukturalnych Realny wpływ na architekturę rozwiązań Możliwość pracy z nowoczesnym stackiem (Kubernetes, GitOps, IaC) Rozwój kompetencji w obszarze platform engineering i cloud-native Elastyczne formy współpracy (B2B / UoP) Przyjazną atmosferę i współpracę z doświadczonym zespołem

🏢 Summary: The role focuses on designing, building, and operating production-grade Kubernetes infrastructure on bare-metal to power large-scale AI and high-performance compute workloads. It involves deep integration of networking, storage, and GPU technologies while ensuring enterprise-grade reliability, automation, and observability across multi-region environments. The position emphasizes Kubernetes internals, infrastructure automation, and SRE practices for mission-critical AI systems. 🗂️ Requirements: 5+ years experience in SRE, DevOps, or infrastructure engineering operating production infrastructure at scale, Hands-on experience building and operating Kubernetes clusters on bare-metal infrastructure, Strong knowledge of Kubernetes internals including CRDs, operators, controllers, admission webhooks, and scheduling, Experience integrating CSI storage, CNI networking, SR-IOV, and GPU device plugins with Kubernetes, Strong Linux systems administration and troubleshooting skills, Proficiency with infrastructure-as-code tools for automation, Solid understanding of networking fundamentals (IPAM, DNS, DHCP, VLAN, VXLAN, routing, load balancing), Experience implementing monitoring and logging solutions in production environments, Understanding of SRE principles including SLIs, SLOs, SLAs, and incident management, Strong scripting skills in Go, Python, or Bash 📃 Skills: Kubernetes, Linux, Terraform, Ansible, Helm, Prometheus, Grafana, ELK, Go, Python, Bash, NVIDIA, SR-IOV, CSI, CNI, Calico, Cilium, Multus, Ceph, InfiniBand, RDMA, RoCE, etcd 🏢 Description: Moonlite delivers high-performance AI infrastructure for organizations running intensive computational research, large-scale model training, and demanding data processing workloads.We provide infrastructure deployed in our facilities or co-located in yours, delivering flexible on-demand or reserved compute that feels like an extension of your existing data center. Our team of AI infrastructure specialists combines bare-metal performance with cloud-native operational simplicity, enabling research teams and enterprises to deploy demanding AI workloads with enterprise-grade reliability and compliance. Your Role: You will be instrumental in building and operating production-grade AI infrastructure with deep Kubernetes expertise at its core. Working closely with our systems engineers, network engineers, and platform engineering team, you'll architect and operate the Kubernetes infrastructure that powers our control plane and orchestrates compute, storage, and networking at scale. This role requires deep understanding of Kubernetes internals, custom resource definitions (CRDs), storage and network integrations, and building production-grade clusters from the ground up (not just deploying in managed environments). You'll ensure enterprise-grade reliability while establishing the automation, observability, and operational practices. Job Responsibilities Kubernetes Infrastructure Engineering: Design, build, and operate production Kubernetes clusters on bare-metal infrastructure – including cluster bootstrapping, control plane architecture, etcd management, and scaling strategies for high-performance compute workloads. Kubernetes Networking & CNIs: Implement and operate custom Kubernetes networking solutions with SR-IOV for high-performance GPU interconnects, multi-tenancy isolation and advanced networking policies. Configure CNI plugins and network segmentation for research workloads. Custom Operators & Controllers: Develop and maintain custom Kubernetes operators and controllers for bare-metal provisioning, infrastructure lifecycle management, and resource orchestration across compute, storage, and networking domains. GPU Infrastructure Integration: Deploy and optimize NVIDIA GPU operators, device plugins, and other custom scheduling logic for GPU workload placement and utilization optimization. Platform Integration & Storage: Build deep integrations between Kubernetes and underlying infrastructure including CSI drivers for storage, custom admission controllers for policy enforcement, and scheduling extensions for specialized hardware placement. Infrastructure Automation: Design and implement automation using Terraform, Ansible, Helm, and custom operators to orchestrate infrastructure workflows and enable deployments across multiple regions. Production Operations & Reliability: Manage production bare-metal infrastructure across multiple regions. Build systems ensuring high availability, fault tolerance, and graceful degradation – establishing SLIs, SLOs, and monitoring to meet enterprise reliability commitments. Observability & Incident Response: Build comprehensive monitoring, logging, and alerting using Prometheus, Grafana, and ELK stack. Lead incident response, conduct postmortems, and implement preventative measures to improve reliability and reduce MTTR. Performance & Capacity Planning: Identify and resolve performance bottlenecks across infrastructure domains. Monitor utilization trends, forecast capacity needs, and optimize resource allocation for various workloads. Requirements Experience: 5+ years in SRE, DevOps, or infrastructure engineering roles with proven experience operating production infrastructure at scale. Kubernetes Infrastructure Expertise: Deep hands-on experience building and operating production Kubernetes clusters on bare-metal infrastructure – not just deploying workloads in managed clusters. Must understand cluster bootstrapping, control plane architecture, etcd operations, and scaling strategies. Kubernetes Internals & Integration: Strong understanding of Kubernetes internals including custom resource definitions (CRDs), operators, controllers, admission webhooks, and scheduling. Experience integrating storage (CSI drivers), networking (CNI, SR-IOV), and specialized hardware (GPU device plugins) with Kubernetes. Linux Systems Experience: Strong fundamentals in Linux systems administration, performance tuning, troubleshooting, and automation in production environments. Infrastructure Automation: Proficiency with infrastructure-as-code tools (Terraform, Ansible, Helm) and building automation to reduce operational overhead. Networking Fundamentals: Solid understanding of networking concepts including IPAM, DNS, DHCP, VLAN/VXLAN, routing, load balancing, and experience troubleshooting network issues in production. Observability & Monitoring: Experience building and maintaining comprehensive monitoring solutions using tools like Prometheus, Grafana, and centralized logging systems. Reliability Practices: Understanding of SRE principles including SLIs/SLOs/SLAs, error budgets, incident management, and blameless postmortems. Scripting & Automation: Strong scripting skills in Go, Python, or Bash for automation, tooling development, and operational efficiency. Problem-Solving Under Pressure: Demonstrated ability to troubleshoot complex issues under pressure, manage incidents effectively, and communicate clearly during outages. Collaboration & Communication: Excellent communication skills and ability to work across teams including systems engineers, network engineers, and software developers. Preferred Qualifications Experience building custom Kubernetes operators or controllers for infrastructure orchestration Deep familiarity with Kubernetes networking (Calico, Cilium, Multus), service mesh technologies, and network policy management Experience with GPU workload orchestration including NVIDIA GPU Operator, MIG, time-slicing, and device plugins Background with advanced Kubernetes features including custom schedulers, admission controllers, and API server extensions Experience with Kubernetes cluster federation or multi-cluster management Knowledge of high-performance networking technologies (InfiniBand, RDMA, RoCE) and their integration with Kubernetes Experience with enterprise storage systems (VAST, Lightbits, Ceph, or similar) Familiarity with configuration management at scale and GitOps practices Understanding of security best practices for Kubernetes and bare-metal infrastructure Experience operating infrastructure in regulated industries or co-located data center environments Background supporting research institutions, technical computing environments, or enterprise AI infrastructure Key Technologies Kubernetes, Linux, Terraform, Ansible, Prometheus, Grafana, ELK Stack, Go, Python, Bash, NVIDIA GPU Technologies, High-Performance Networking, Enterprise Storage Systems Why Moonlite Build Critical Research Infrastructure: Your work will directly enable quantitative research teams and AI practitioners to push the boundaries of what's possible in financial modeling and AI research. Enterprise Impact: Build and operate infrastructure that supports mission-critical research and AI workloads for leading financial institutions and research organizations. Technical Excellence: Join an infrastructure team focused on delivering enterprise-grade reliability while pushing the boundaries of high-performance computing capabilities. Hands-On Ownership: As part of our growing infrastructure team, you'll have significant ownership over critical systems and the autonomy to influence our operational practices and technology choices. Industry Leadership: Work alongside experienced infrastructure professionals who have built and operated systems for the most demanding computing environments. We offer a competitive total compensation package combining a competitive base salary, startup equity, and industry-leading benefits. The total compensation range for this role is $165,000 – $225,000, which includes both base salary and equity. Actual compensation will be determined based on experience, skills, and market alignment. We provide generous benefits, including a 6% 401(k) match, fully covered health insurance premiums, and other comprehensive offerings to support your well-being and success as we grow together. #li-remote

🏢 Summary: Leadership role within Infrastructure Reliability Engineering focused on managing Kubernetes-based container platforms and cloud environments while ensuring high availability and production stability. The position combines hands-on technical work with team leadership, covering observability, automation, incident management, and security remediation. You will drive resilience, scalability, and continuous improvement of mission-critical infrastructure. 🗂️ Requirements: Minimum 8 years relevant IT experience, Minimum 5 years System Administration experience, Minimum 5 years Container and Cloud experience (AWS, GCP), Minimum 4 years hands-on Kubernetes experience, Minimum 3 years scripting experience, Minimum 2 years AWS or GCP experience, Experience with microservices traffic routing, Experience with CI/CD or GitOps pipelines, Experience with configuration management tools, Knowledge of ITIL processes (Incident, Change, Problem, Release Management), Strong knowledge of networking concepts, Experience with monitoring and logging tools, Bachelor’s degree in Engineering, Computer Science, Information Systems or related field 📃 Skills: Kubernetes, AWS, GCP, Docker, Istio, Helm, Kubeadm, CSI, CNI, ArgoCD, Jenkins, CodeFresh, Prometheus, Grafana, Fluentbit, Netcool, Humio, Ansible, Terraform, Chef, Python, Shell, YAML, GitOps, CI/CD, ITIL, Microservices, OpenAI, Claude, Networking 🏢 Description: About Us Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you. Job Description As a member of the Infrastructure Reliability Engineering team – You are responsible to manage a team of system engineers who focused on Kubernetes, microservices architecture, and cloud technologies. As part of this self-driven team, you will support critical container Infrastructure and ensure the stability of services by performing dedicated maintenance activities. You engage in automation activities, perform root cause analysis (RCA), and remediation. Knowledge of production support process including incident/change/problem management, call triaging, and critical issue resolution procedures. Essential Functions: Infrastructure life cycle management and Production Support of container, cloud technologies and orchestration platforms Strong technical analytical and troubleshooting skills and possess the ability to explain technical concepts and provide guidance to staff. Develop and implement a comprehensive observability strategy to enhance the organization's ability to monitor, detect, and respond to potential issues proactively. Leverage data analytics to identify trends, patterns, and anomalies in system behavior, providing actionable insights for continuous improvement. Drive initiatives to enhance IT infrastructure resilience, scalability, and security. Provide strong leadership with a focus on attracting, motivating, and developing best-in-class talent. Mentor and coach teams to develop future leaders in alignment with company objectives. Balance both leading a team and engaging directly with the work needed to accomplish objectives. Assist direct reports with ongoing prioritization and resource allocation to ensure that the crucial business initiatives are delivered. Utilize leadership skills, problem solving and decision-making skills to facilitate and encourage participation of team members to meet objectives in congruence with approved standards and guidelines. Be a leader that continually raises the bar for others. Ability to operate in complex, highly secure, and highly available, operations environments and interact with the technology domain experts required to maintain those environments. Excellent communication & interpersonal skills. Coaching other members of the support team, sharing technical and customer knowledge in a helpful and timely fashion Responsible for partnering with the Platform, Engineering and Delivery Teams to deliver seamless infrastructure support for all Visa business lines. Work closely with geographically distributed teams on technical challenges and process improvements. Security Remediation process (vulnerability assessment and patch management) Responsible for adherence of established ITIL practice such as Incident, Change, Problem and Release Management Be scheduled On-Call to support the infrastructure and our systems. This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager. Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager. Qualifications Basic Qualifications: 8+ years of relevant work experience with a Bachelor’s Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD, OR 11+ years of relevant work experience. Preferred Qualifications: 9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD Minimum Bachelor's degree in Engineering, or Computer Science, Information Systems, or related field Minimum Eight (8) years of directly related experience. In-depth knowledge of IT infrastructure, observability tools, data analytics, and incident management processes. Minimum 5 years of experience in System Administration At least 5 years in the Container and Cloud (AWS & GCP) with a focus on DevOps and service-based systems engineering. Minimum 4 years hands-on experience with Kubernetes (on internals architecture of K8s). Minimum 2 years of experience with AWS /GCP Minimum 3 years of Scripting experience (Shell, Python, Ansible, Terraform and YAML packages) Minimum 2 years of experience with Microservices based applications traffic routing (i.e., Istio ServiceMesh) Experience with configuration management tools (Chef, Ansible, terraform etc.) is must. Working with tools surrounding the Kubernetes ecosystem such as helm, kubeadm, CSI, CNI etc. is must. Experience with CI/CD or GitOps pipeline Architecture (i.e., ArgoCD, Code Fresh, Jenkins) is must. Working knowledge of monitoring and logging tools: Prometheus, Graphana, Fluentbit ,Netcool, Humio Exposure to AI platforms (OpenAI, Claude) or interest in AI-driven automation for Container operations. Deep understanding of networking concepts Visa is an EEO Employer Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

🏢 Summary: Platform Engineer role focused on building and operating AWS-based, Kubernetes-driven infrastructure in an AI-first environment. The position involves supporting AI-powered applications, migrating services to EKS, and delivering Infrastructure-as-Code while ensuring scalability, reliability, and observability. You will work in a global team bridging AI solutions with stable production cloud platforms. 🗂️ Requirements: Proficiency in at least one programming or scripting language (Python, Node.js or TypeScript), Hands-on experience with AWS (including ECS) and migration to Kubernetes/EKS, Strong knowledge of Kubernetes (EKS), Experience with Terraform for Infrastructure-as-Code, Experience with CI/CD pipelines (GitHub Actions preferred), Experience with GitOps approach (ArgoCD or similar), Experience with monitoring and observability tools (Datadog, Prometheus or similar), Experience with MongoDB (Atlas), Experience with AI-assisted development tools (Claude Code), AI-first mindset and openness to AI-driven automation 📃 Skills: AWS, ECS, Kubernetes, EKS, Terraform, Python, Node.js, TypeScript, GitHub, Actions, ArgoCD, Datadog, Prometheus, MongoDB, Atlas, Claude, Temporal 🏢 Description: Holisticon Connect is a division within NEXER GROUP - a custom software development company. We started in Poland in 2017 and are now a team of over 140 people. We have the opportunity to work with world-renowned brands from Scandinavia, the UK, and Western Europe. Our goal is to grow stronger, in competence rather than in numbers. If you like what we do, check out our offer, maybe we will have the pleasure of meeting you! 😊 Join a global initiative that’s redefining how AI transforms business. 📝 We are looking for a Platform Engineer (Kubernetes, AWS, AI-first environment), who combines strong cloud‑native engineering skills with a genuine interest in AI‑driven solutions . You will be joining one of the global leaders in AI‑powered video solutions for enterprise. As part of this environment, you will work within a global team responsible for building and maintaining the infrastructure that powers intelligent agents, foundation models , and automated workflows used across the organization. Your work will bridge the fast‑evolving AI ecosystem with stable, scalable, and well‑observed production environments. Your role: Designing, operating, and continuously improving AWS-based infrastructure, supporting customer-facing applications - with a strong focus on ongoing migration of customer-facing services to Kubernetes (EKS). Delivering Infrastructure‑as‑Code using Terraform. Managing Kubernetes clusters (EKS) deployments to ensure scalable and reliable environments. Using agentic tools such as Claude Code to streamline development processes and automate cloud‑based AI and non-AI workflows. Building monitoring, logging, metrics, and observability pipelines dedicated to AI‑powered and non-AI workflows. Contributing to technical decisions through RFC-based processes, where proposals are peer-reviewed to ensure alignment before implementation. Operating with a high level of autonomy - taking ownership of solutions, proactively navigating ambiguity, and making day-to-day technical decisions within the team, while aligning changes through discussion and consensus. 👉 We offer a choice of employment form: B2B B2B: 150 – 175 PLN net/hour + VAT ✅ You might be the perfect match if you are/have: Proficiency in at least one programming or scripting language (e.g., Python, Node.js, TypeScript ) and hands‑on experience with AI‑assisted development tools such as Claude Code. Hands-on experience with AWS cloud (including ECS; understanding migration towards Kubernetes/EKS). Experience with CI/CD pipelines (preferably GitHub Actions). Experience with GitOps approach (e.g., ArgoCD). Strong Kubernetes knowledge (EKS) , CKA certification is a bonus. Practical experience using Terraform to provision and manage cloud infrastructure. Experience with monitoring and observability tools (e.g., Datadog , Prometheus or equivalent). Experience with MongoDB (especially Atlas). AI-first mindset - openness to AI-driven development and automation is required; candidates strongly opposed to AI/agentic approaches will not be considered. Experience with Temporal or similar workflow orchestration tools – nice to have. 💡By joining us, you gain the following: Opportunity to work on exciting, international projects in cutting-edge industries like Automotive, Biotech, IoT; Possibility to develop in cloud technologies; Becoming part of a team that believes that the next step to a promising future is to put your heart into it and make it happen; Respect for your private life so you don't have to work overtime or on weekends; Team Events budget to socialize outside of work; Company Events to celebrate smaller and bigger successes (Summer Party, Programmer's Day, and trips abroad – so far we've been in Cape Town, Are, and Barcelona). 🚀 Perks and benefits: Fully remote work or in our office in Wrocław; Free benefits such as Luxmed , Multisport , and life insurance in Nationale Nederlanden ; Attractive referral system (9,5k for senior, 6k for mid, 2,5k for junior); Personal Training Budget with additional paid hours; Passion Day - an extra day off for your hobby to spend as you please; Flexible working hours with no micro-management approach. Our core hours are 9-15, the rest of the working time is up to you; We provide high-quality work equipment + 2 additional monitors and accessories. 📌 If you apply for this position and match our expectations, then: 1) You will be invited to an HR Screening with our IT Recruiter. 2) You will have a technical interview with customer. Submit your application online in one easy step! Apply now!