Вакансии

Location: Republic of Ireland (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with LLMs, prompt engineering, and building applications powered by GenAI. Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building or working with agent frameworks or multi‑agent workflows. Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks) Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In the Republic of Ireland, the Base compensation range for this role is EUR 107,000 - EUR 134,000 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Sweden (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with LLMs, prompt engineering, and building applications powered by GenAI. Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building or working with agent frameworks or multi‑agent workflows. Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks) Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In Sweden, the Base compensation range for this role is SEK 878,578 - SEK 1,054,294 .  Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Spain (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity, and we would be interested in applicants located in Spain, Sweden, UK, Ireland or Germany. The Opportunity: At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Staff-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. What You'll Be Doing: Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What Makes You a Great Fit: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Experience with LLMs, prompt engineering, and building applications powered by GenAI. Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Bonus Points for: Experience building or working with agent frameworks or multi‑agent workflows. Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks) Experience building tools for data engineering. How we work: We are a remote-first team that meets regularly over video and does most of our work asynchronously, in writing. We value creativity, diverse perspectives, and clear communication. Tempo is relied upon by prominent global organizations to monitor critical applications and infrastructure, and we expect everyone on the team, including our Staff engineers, to contribute ideas that make it a more reliable, more useful, and more loved product. Compensation & Rewards: In Spain, the Base compensation range for this role is EUR 94,025 - EUR 112,830 . Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Задачи: — Разрабатывать и поддерживать интеграции с платёжными и финансовыми сервисами (REST / SOAP API, OAuth, API-key / Bearer); — Подключать новых провайдеров, валюты и страны, развивать pay-in / pay-out flows; — Проектировать и реализовывать REST API на Node.js + TypeScript + Express; — Реализовывать webhooks: signature / HMAC verification, idempotency, deduplication, retries; — Разбираться с проблемами интеграций (таймауты, частичные отказы, нестабильность API); — Работать с NoSQL: моделирование данных, индексы, транзакции; — Поддерживать KYC / AML интеграции; — Писать unit / integration tests и участвовать в code review; — Деплоить и поддерживать сервисы в облаке, разбирать production-инциденты. Требования: — Опыт коммерческой разработки на Node.js + TypeScript от 3 лет; — Практический опыт в Fintech / Payments / Banking / payment-heavy e-commerce от 1 года; — Опыт разработки и поддержки интеграций с внешними API (REST и SOAP); — Уверенное понимание HTTP / HTTPS, REST API, webhooks, authentication и status codes; — Практический опыт с idempotency, retries, deduplication и HMAC / signature verification; — Опыт работы с NoSQL; — Понимание денежных расчётов и проблем floating point (опыт с BigNumber / Decimal или аналогами); — Опыт работы с Docker и деплоя backend-сервисов в GCP / AWS / Azure. Будет плюсом: — Интеграции с международными платёжными, крипто- или KYC-провайдерами; — Практическое знание AML / KYC, 3DS 2.0, chargebacks, reversals; — Опыт работы с несколькими провайдерами и fallback / routing logic; — Опыт работы с микросервисной архитектурой, очередями, contract testing; — Базовый React (чтобы при необходимости читать/менять существующий код); — Использование AI-инструментов для разработки.

Location: India Job Overview We are seeking an experienced AI Solution Architect to design and lead end-to-end enterprise AI Factory and GPU infrastructure solutions spanning compute, high-performance networking, storage, Kubernetes, cloud, and AI/ML platforms. The role requires strong expertise in NVIDIA GPU technologies, AI workloads, scalable infrastructure architecture, security, observability, performance engineering, and capacity planning . Key Responsibilities Own end-to-end architecture for AI Factory and enterprise AI solutions from requirements through production readiness. Assess AI/ML workload requirements for training, fine-tuning, inference, batch processing, and high-performance computing. Design GPU compute architectures including NVIDIA HGX/DGX/OEM platforms, multi-GPU systems, NVLink/NVSwitch, and GPU resource allocation. Design high-performance AI networking using 100/200/400/800G Ethernet, EVPN/VXLAN, and leaf-spine architectures. Design AI storage and data architectures using object storage, parallel file systems  like  Ceph, WEKA, , or equivalent platforms. Define AI platform architecture across Kubernetes, HPC, container runtimes, model-serving platforms, and enterprise AI frameworks. Establish architecture standards for security, identity, tenant isolation, data protection, observability, disaster recovery, and operational resilience. Develop reference architectures, high-level/low-level designs, capacity models, bills of materials, technology evaluations, and implementation roadmaps. Lead technical evaluations, proof-of-concepts, vendor assessments, and architecture review boards. Collaborate with infrastructure, network, security, storage, cloud, data, application, and operations teams. Define performance, availability, scalability, security, and cost objectives and validate architecture against measurable acceptance criteria. Provide technical leadership during deployment, migration, integration, troubleshooting, and production transition. • Required Technical Skills AI / ML Architecture • NVIDIA AI Enterprise, NGC, CUDA, NCCL, DCGM, GPU Operator and AI platform ecosystem. • PyTorch, TensorFlow, JAX and operational understanding of training and inference workloads. • GPU scheduling, multi-tenancy, MIG/vGPU, GPU utilization and workload placement. • LLM, generative AI, RAG, fine-tuning, model serving and inference architecture. GPU & AI Factory Infrastructure • NVIDIA A100/H100/H200/B200 or equivalent GPU platforms; familiarity with next-generation systems. • NVLink, NVSwitch, PCIe topology and multi-GPU performance architecture. • DGX/HGX/OEM GPU server architecture and lifecycle management. • AI Factory capacity planning, rack density, power, cooling, commissioning and lifecycle strategy. High-Performance Networking • 100/200/400/800G Ethernet, InfiniBand, RoCEv2 and RDMA, Netris • NVIDIA ConnectX/SuperNIC, Spectrum/Spectrum-X, Quantum and BlueField DPU technologies. • BGP, EVPN/VXLAN, VRF, ECMP, VLAN, MTU, PFC, ECN, QoS and congestion management. • GPU east-west traffic, GPUDirect RDMA and network performance troubleshooting. AI Storage & Data Architecture • Parallel file systems, object storage, NFS, NVMe/NVMe-oF and high-throughput data pipelines. • Ceph, WEKA, VAST, Dell PowerScale, Pure FlashBlade, NetApp or equivalent technologies. • Data lake/lakehouse concepts, metadata, lineage, data movement and data lifecycle. • GPUDirect Storage and storage/network performance optimization. AI Platform & Orchestration • Kubernetes, GPU Operator, container runtimes and Kubernetes GPU scheduling. • HPC or other equivalent workload schedulers. • Model serving/inference platforms and MLOps platform architecture. • API gateways, service discovery, secrets management and platform integration. Cloud & Hybrid Architecture • AWS and/or Azure AI infrastructure and security services. • Hybrid cloud connectivity, IAM, private networking, cloud storage and workload placement. • Cloud cost optimization, capacity planning and FinOps considerations for GPU workloads. Security & Governance • Zero Trust, network segmentation, IAM/RBAC, PAM and workload identity. • GPU, DPU, container, Kubernetes, firmware and supply-chain security. • Encryption at rest/in transit, secrets management, audit logging and compliance controls. • AI-specific risks including data/model protection, tenant isolation and secure model access. Observability & Reliability • Prometheus, Grafana, OpenTelemetry, NVIDIA DCGM and infrastructure telemetry. • Monitoring across GPU, CPU, memory, network, storage, power and thermal domains. • High availability, backup/restore, disaster recovery, business continuity and failure-domain design. • Performance engineering, bottleneck analysis, SLO/SLA design and capacity forecasting. Architecture Deliverables • AI Factory reference architecture and solution blueprints • High-Level Design (HLD) and Low-Level Design (LLD) • Network, compute, GPU and storage architecture diagrams • Capacity, performance and scalability models • Technology evaluation and vendor comparison documents • Security architecture and threat-model inputs • Bill of Materials (BOM) and infrastructure sizing • Migration/deployment strategy and implementation roadmap • Operational readiness checklist, runbooks and acceptance criteria Experience & Qualifications • 10+ years of infrastructure, cloud, enterprise architecture or solution architecture experience, with significant AI/GPU infrastructure exposure. • Proven experience designing large-scale enterprise platforms and translating business requirements into technical architectures. • Hands-on understanding of physical infrastructure, GPU systems, networking, storage and Linux platforms. • Bachelor's degree in Computer Science, Engineering, Information Technology or related field preferred. Preferred Certifications • NVIDIA certifications or equivalent GPU/AI infrastructure credentials • AWS Solutions Architect / Azure Solutions Architect • TOGAF or equivalent enterprise architecture certification • CCNP/CCIE or equivalent networking certification • CISSP or equivalent security certification • Kubernetes certifications such as CKA/CKAD • Red Hat / Linux certifications

Location: India Job Overview We are looking for an experienced Network Security Engineer to design, implement, monitor, and support enterprise security infrastructure across on-premises, cloud, and hybrid environments. The ideal candidate should possess strong expertise in next-generation firewalls, SIEM platforms, cloud security, Zero Trust architecture, and modern cybersecurity operations. The role requires hands-on experience with technologies such as Fortinet, SonicWall, Palo Alto Networks, SIEM solutions, SASE, SD-WAN, endpoint security, and threat detection platforms. Key Responsibilities Design, deploy, and manage enterprise network security solutions Configure and administer Fortinet, SonicWall, and Palo Alto firewalls Implement and maintain VPNs, IPS/IDS, web filtering, NAT, ACLs, and segmentation policies Monitor security events using SIEM, XDR, and SOC monitoring platforms Investigate security incidents, perform threat analysis, and support incident response activities Manage firewall policies, security rules, and compliance controls Implement Zero Trust Network Access (ZTNA) and identity-based security controls Support cloud security initiatives across AWS, Azure, and hybrid infrastructure Configure and support SD-WAN and Secure Access Service Edge (SASE) solutions Conduct vulnerability assessments and remediation activities Collaborate with infrastructure, cloud, and application teams to secure enterprise environments Maintain security documentation, diagrams, SOPs, and audit records Participate in on-call rotations and critical incident handling GPU East-West and North-South traffic control and security AI networking and security integration expertise Understanding of AI infrastructure design and reference architectures SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Compliance with industry frameworks and standards such as NIST, ISO, etc. Required Skills & Technologies Firewall & Network Security Fortinet FortiGate SonicWall Palo Alto Networks Check Point (preferred) Cisco Firepower / ASA VPN Technologies (IPSec / SSL VPN) IDS/IPS Web Application Firewall (WAF) NAC (Network Access Control) Modern Security Technologies Zero Trust Architecture (ZTA) ZTNA (Zero Trust Network Access) SASE (Secure Access Service Edge) SD-WAN Security SSE (Security Service Edge) CASB (Cloud Access Security Broker) Micro-segmentation Secure Remote Access Solutions SIEM, SOC & Threat Detection Experience with one or more: Splunk QRadar Microsoft Sentinel LogRhythm ArcSight Elastic SIEM Knowledge of: SOC operations Threat hunting Log correlation MITRE ATT&CK framework Incident response Threat intelligence integration Cloud & Infrastructure Security AWS Security Microsoft Azure Security Hybrid cloud networking Cloud firewall management Security Groups / NSGs Identity & Access Management (IAM) Endpoint & Advanced Security EDR/XDR platforms CrowdStrike Microsoft Defender SentinelOne Endpoint hardening DLP (Data Loss Prevention) Email security solutions Networking Fundamentals Strong understanding of: TCP/IP Routing & Switching VLANs BGP / OSPF DNS / DHCP Load Balancing Network troubleshooting Automation & Scripting (Preferred) Python PowerShell Bash scripting Security automation SOAR platforms Preferred Certifications Fortinet NSE / FCP Palo Alto PCNSA / PCNSE CCNP Security CISSP CEH CompTIA Security+ Microsoft SC Certifications AWS Security Specialty Education Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, or related field preferred. Soft Skills Strong analytical and troubleshooting skills Ability to work in high-pressure environments Excellent communication and stakeholder management Strong documentation and reporting abilities Proactive mindset with focus on continuous improvement

Location: Malaysia Job Overview We are looking for an experienced Network Security Engineer to design, implement, monitor, and support enterprise security infrastructure across on-premises, cloud, and hybrid environments. The ideal candidate should possess strong expertise in next-generation firewalls, SIEM platforms, cloud security, Zero Trust architecture, and modern cybersecurity operations. The role requires hands-on experience with technologies such as Fortinet, SonicWall, Palo Alto Networks, SIEM solutions, SASE, SD-WAN, endpoint security, and threat detection platforms. Key Responsibilities Design, deploy, and manage enterprise network security solutions Configure and administer Fortinet, SonicWall, and Palo Alto firewalls Implement and maintain VPNs, IPS/IDS, web filtering, NAT, ACLs, and segmentation policies Monitor security events using SIEM, XDR, and SOC monitoring platforms Investigate security incidents, perform threat analysis, and support incident response activities Manage firewall policies, security rules, and compliance controls Implement Zero Trust Network Access (ZTNA) and identity-based security controls Support cloud security initiatives across AWS, Azure, and hybrid infrastructure Configure and support SD-WAN and Secure Access Service Edge (SASE) solutions Conduct vulnerability assessments and remediation activities Collaborate with infrastructure, cloud, and application teams to secure enterprise environments Maintain security documentation, diagrams, SOPs, and audit records Participate in on-call rotations and critical incident handling GPU East-West and North-South traffic control and security AI networking and security integration expertise Understanding of AI infrastructure design and reference architectures SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Compliance with industry frameworks and standards such as NIST, ISO, etc. Required Skills & Technologies Firewall & Network Security Fortinet FortiGate SonicWall Palo Alto Networks Check Point (preferred) Cisco Firepower / ASA VPN Technologies (IPSec / SSL VPN) IDS/IPS Web Application Firewall (WAF) NAC (Network Access Control) Modern Security Technologies Zero Trust Architecture (ZTA) ZTNA (Zero Trust Network Access) SASE (Secure Access Service Edge) SD-WAN Security SSE (Security Service Edge) CASB (Cloud Access Security Broker) Micro-segmentation Secure Remote Access Solutions SIEM, SOC & Threat Detection Experience with one or more: Splunk QRadar Microsoft Sentinel LogRhythm ArcSight Elastic SIEM Knowledge of: SOC operations Threat hunting Log correlation MITRE ATT&CK framework Incident response Threat intelligence integration Cloud & Infrastructure Security AWS Security Microsoft Azure Security Hybrid cloud networking Cloud firewall management Security Groups / NSGs Identity & Access Management (IAM) Endpoint & Advanced Security EDR/XDR platforms CrowdStrike Microsoft Defender SentinelOne Endpoint hardening DLP (Data Loss Prevention) Email security solutions Networking Fundamentals Strong understanding of: TCP/IP Routing & Switching VLANs BGP / OSPF DNS / DHCP Load Balancing Network troubleshooting Automation & Scripting (Preferred) Python PowerShell Bash scripting Security automation SOAR platforms Preferred Certifications Fortinet NSE / FCP Palo Alto PCNSA / PCNSE CCNP Security CISSP CEH CompTIA Security+ Microsoft SC Certifications AWS Security Specialty Education Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, or related field preferred. Soft Skills Strong analytical and troubleshooting skills Ability to work in high-pressure environments Excellent communication and stakeholder management Strong documentation and reporting abilities Proactive mindset with focus on continuous improvement

Location: Singapore Job Overview We are looking for an experienced Network Security Engineer to design, implement, monitor, and support enterprise security infrastructure across on-premises, cloud, and hybrid environments. The ideal candidate should possess strong expertise in next-generation firewalls, SIEM platforms, cloud security, Zero Trust architecture, and modern cybersecurity operations. The role requires hands-on experience with technologies such as Fortinet, SonicWall, Palo Alto Networks, SIEM solutions, SASE, SD-WAN, endpoint security, and threat detection platforms. Key Responsibilities Design, deploy, and manage enterprise network security solutions Configure and administer Fortinet, SonicWall, and Palo Alto firewalls Implement and maintain VPNs, IPS/IDS, web filtering, NAT, ACLs, and segmentation policies Monitor security events using SIEM, XDR, and SOC monitoring platforms Investigate security incidents, perform threat analysis, and support incident response activities Manage firewall policies, security rules, and compliance controls Implement Zero Trust Network Access (ZTNA) and identity-based security controls Support cloud security initiatives across AWS, Azure, and hybrid infrastructure Configure and support SD-WAN and Secure Access Service Edge (SASE) solutions Conduct vulnerability assessments and remediation activities Collaborate with infrastructure, cloud, and application teams to secure enterprise environments Maintain security documentation, diagrams, SOPs, and audit records Participate in on-call rotations and critical incident handling GPU East-West and North-South traffic control and security AI networking and security integration expertise Understanding of AI infrastructure design and reference architectures SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Compliance with industry frameworks and standards such as NIST, ISO, etc. Required Skills & Technologies Firewall & Network Security Fortinet FortiGate SonicWall Palo Alto Networks Check Point (preferred) Cisco Firepower / ASA VPN Technologies (IPSec / SSL VPN) IDS/IPS Web Application Firewall (WAF) NAC (Network Access Control) Modern Security Technologies Zero Trust Architecture (ZTA) ZTNA (Zero Trust Network Access) SASE (Secure Access Service Edge) SD-WAN Security SSE (Security Service Edge) CASB (Cloud Access Security Broker) Micro-segmentation Secure Remote Access Solutions SIEM, SOC & Threat Detection Experience with one or more: Splunk QRadar Microsoft Sentinel LogRhythm ArcSight Elastic SIEM Knowledge of: SOC operations Threat hunting Log correlation MITRE ATT&CK framework Incident response Threat intelligence integration Cloud & Infrastructure Security AWS Security Microsoft Azure Security Hybrid cloud networking Cloud firewall management Security Groups / NSGs Identity & Access Management (IAM) Endpoint & Advanced Security EDR/XDR platforms CrowdStrike Microsoft Defender SentinelOne Endpoint hardening DLP (Data Loss Prevention) Email security solutions Networking Fundamentals Strong understanding of: TCP/IP Routing & Switching VLANs BGP / OSPF DNS / DHCP Load Balancing Network troubleshooting Automation & Scripting (Preferred) Python PowerShell Bash scripting Security automation SOAR platforms Preferred Certifications Fortinet NSE / FCP Palo Alto PCNSA / PCNSE CCNP Security CISSP CEH CompTIA Security+ Microsoft SC Certifications AWS Security Specialty Education Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, or related field preferred. Soft Skills Strong analytical and troubleshooting skills Ability to work in high-pressure environments Excellent communication and stakeholder management Strong documentation and reporting abilities Proactive mindset with focus on continuous improvement

Location: United States Job Overview We are looking for an experienced Network Security Engineer to design, implement, monitor, and support enterprise security infrastructure across on-premises, cloud, and hybrid environments. The ideal candidate should possess strong expertise in next-generation firewalls, SIEM platforms, cloud security, Zero Trust architecture, and modern cybersecurity operations. The role requires hands-on experience with technologies such as Fortinet, SonicWall, Palo Alto Networks, SIEM solutions, SASE, SD-WAN, endpoint security, and threat detection platforms. Key Responsibilities Design, deploy, and manage enterprise network security solutions Configure and administer Fortinet, SonicWall, and Palo Alto firewalls Implement and maintain VPNs, IPS/IDS, web filtering, NAT, ACLs, and segmentation policies Monitor security events using SIEM, XDR, and SOC monitoring platforms Investigate security incidents, perform threat analysis, and support incident response activities Manage firewall policies, security rules, and compliance controls Implement Zero Trust Network Access (ZTNA) and identity-based security controls Support cloud security initiatives across AWS, Azure, and hybrid infrastructure Configure and support SD-WAN and Secure Access Service Edge (SASE) solutions Conduct vulnerability assessments and remediation activities Collaborate with infrastructure, cloud, and application teams to secure enterprise environments Maintain security documentation, diagrams, SOPs, and audit records Participate in on-call rotations and critical incident handling GPU East-West and North-South traffic control and security AI networking and security integration expertise Understanding of AI infrastructure design and reference architectures SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Compliance with industry frameworks and standards such as NIST, ISO, etc. Required Skills & Technologies Firewall & Network Security Fortinet FortiGate SonicWall Palo Alto Networks Check Point (preferred) Cisco Firepower / ASA VPN Technologies (IPSec / SSL VPN) IDS/IPS Web Application Firewall (WAF) NAC (Network Access Control) Modern Security Technologies Zero Trust Architecture (ZTA) ZTNA (Zero Trust Network Access) SASE (Secure Access Service Edge) SD-WAN Security SSE (Security Service Edge) CASB (Cloud Access Security Broker) Micro-segmentation Secure Remote Access Solutions SIEM, SOC & Threat Detection Experience with one or more: Splunk QRadar Microsoft Sentinel LogRhythm ArcSight Elastic SIEM Knowledge of: SOC operations Threat hunting Log correlation MITRE ATT&CK framework Incident response Threat intelligence integration Cloud & Infrastructure Security AWS Security Microsoft Azure Security Hybrid cloud networking Cloud firewall management Security Groups / NSGs Identity & Access Management (IAM) Endpoint & Advanced Security EDR/XDR platforms CrowdStrike Microsoft Defender SentinelOne Endpoint hardening DLP (Data Loss Prevention) Email security solutions Networking Fundamentals Strong understanding of: TCP/IP Routing & Switching VLANs BGP / OSPF DNS / DHCP Load Balancing Network troubleshooting Automation & Scripting (Preferred) Python PowerShell Bash scripting Security automation SOAR platforms Preferred Certifications Fortinet NSE / FCP Palo Alto PCNSA / PCNSE CCNP Security CISSP CEH CompTIA Security+ Microsoft SC Certifications AWS Security Specialty Education Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, or related field preferred. Soft Skills Strong analytical and troubleshooting skills Ability to work in high-pressure environments Excellent communication and stakeholder management Strong documentation and reporting abilities Proactive mindset with focus on continuous improvement

Location: Serbia Job Overview We are looking for an experienced Network Security Engineer to design, implement, monitor, and support enterprise security infrastructure across on-premises, cloud, and hybrid environments. The ideal candidate should possess strong expertise in next-generation firewalls, SIEM platforms, cloud security, Zero Trust architecture, and modern cybersecurity operations. The role requires hands-on experience with technologies such as Fortinet, SonicWall, Palo Alto Networks, SIEM solutions, SASE, SD-WAN, endpoint security, and threat detection platforms. Key Responsibilities Design, deploy, and manage enterprise network security solutions Configure and administer Fortinet, SonicWall, and Palo Alto firewalls Implement and maintain VPNs, IPS/IDS, web filtering, NAT, ACLs, and segmentation policies Monitor security events using SIEM, XDR, and SOC monitoring platforms Investigate security incidents, perform threat analysis, and support incident response activities Manage firewall policies, security rules, and compliance controls Implement Zero Trust Network Access (ZTNA) and identity-based security controls Support cloud security initiatives across AWS, Azure, and hybrid infrastructure Configure and support SD-WAN and Secure Access Service Edge (SASE) solutions Conduct vulnerability assessments and remediation activities Collaborate with infrastructure, cloud, and application teams to secure enterprise environments Maintain security documentation, diagrams, SOPs, and audit records Participate in on-call rotations and critical incident handling GPU East-West and North-South traffic control and security AI networking and security integration expertise Understanding of AI infrastructure design and reference architectures SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Compliance with industry frameworks and standards such as NIST, ISO, etc. Required Skills & Technologies Firewall & Network Security Fortinet FortiGate SonicWall Palo Alto Networks Check Point (preferred) Cisco Firepower / ASA VPN Technologies (IPSec / SSL VPN) IDS/IPS Web Application Firewall (WAF) NAC (Network Access Control) Modern Security Technologies Zero Trust Architecture (ZTA) ZTNA (Zero Trust Network Access) SASE (Secure Access Service Edge) SD-WAN Security SSE (Security Service Edge) CASB (Cloud Access Security Broker) Micro-segmentation Secure Remote Access Solutions SIEM, SOC & Threat Detection Experience with one or more: Splunk QRadar Microsoft Sentinel LogRhythm ArcSight Elastic SIEM Knowledge of: SOC operations Threat hunting Log correlation MITRE ATT&CK framework Incident response Threat intelligence integration Cloud & Infrastructure Security AWS Security Microsoft Azure Security Hybrid cloud networking Cloud firewall management Security Groups / NSGs Identity & Access Management (IAM) Endpoint & Advanced Security EDR/XDR platforms CrowdStrike Microsoft Defender SentinelOne Endpoint hardening DLP (Data Loss Prevention) Email security solutions Networking Fundamentals Strong understanding of: TCP/IP Routing & Switching VLANs BGP / OSPF DNS / DHCP Load Balancing Network troubleshooting Automation & Scripting (Preferred) Python PowerShell Bash scripting Security automation SOAR platforms Preferred Certifications Fortinet NSE / FCP Palo Alto PCNSA / PCNSE CCNP Security CISSP CEH CompTIA Security+ Microsoft SC Certifications AWS Security Specialty Education Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, or related field preferred. Soft Skills Strong analytical and troubleshooting skills Ability to work in high-pressure environments Excellent communication and stakeholder management Strong documentation and reporting abilities Proactive mindset with focus on continuous improvement

Location: Romania Job Overview We are looking for an experienced Network Security Engineer to design, implement, monitor, and support enterprise security infrastructure across on-premises, cloud, and hybrid environments. The ideal candidate should possess strong expertise in next-generation firewalls, SIEM platforms, cloud security, Zero Trust architecture, and modern cybersecurity operations. The role requires hands-on experience with technologies such as Fortinet, SonicWall, Palo Alto Networks, SIEM solutions, SASE, SD-WAN, endpoint security, and threat detection platforms. Key Responsibilities Design, deploy, and manage enterprise network security solutions Configure and administer Fortinet, SonicWall, and Palo Alto firewalls Implement and maintain VPNs, IPS/IDS, web filtering, NAT, ACLs, and segmentation policies Monitor security events using SIEM, XDR, and SOC monitoring platforms Investigate security incidents, perform threat analysis, and support incident response activities Manage firewall policies, security rules, and compliance controls Implement Zero Trust Network Access (ZTNA) and identity-based security controls Support cloud security initiatives across AWS, Azure, and hybrid infrastructure Configure and support SD-WAN and Secure Access Service Edge (SASE) solutions Conduct vulnerability assessments and remediation activities Collaborate with infrastructure, cloud, and application teams to secure enterprise environments Maintain security documentation, diagrams, SOPs, and audit records Participate in on-call rotations and critical incident handling GPU East-West and North-South traffic control and security AI networking and security integration expertise Understanding of AI infrastructure design and reference architectures SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Compliance with industry frameworks and standards such as NIST, ISO, etc. Required Skills & Technologies Firewall & Network Security Fortinet FortiGate SonicWall Palo Alto Networks Check Point (preferred) Cisco Firepower / ASA VPN Technologies (IPSec / SSL VPN) IDS/IPS Web Application Firewall (WAF) NAC (Network Access Control) Modern Security Technologies Zero Trust Architecture (ZTA) ZTNA (Zero Trust Network Access) SASE (Secure Access Service Edge) SD-WAN Security SSE (Security Service Edge) CASB (Cloud Access Security Broker) Micro-segmentation Secure Remote Access Solutions SIEM, SOC & Threat Detection Experience with one or more: Splunk QRadar Microsoft Sentinel LogRhythm ArcSight Elastic SIEM Knowledge of: SOC operations Threat hunting Log correlation MITRE ATT&CK framework Incident response Threat intelligence integration Cloud & Infrastructure Security AWS Security Microsoft Azure Security Hybrid cloud networking Cloud firewall management Security Groups / NSGs Identity & Access Management (IAM) Endpoint & Advanced Security EDR/XDR platforms CrowdStrike Microsoft Defender SentinelOne Endpoint hardening DLP (Data Loss Prevention) Email security solutions Networking Fundamentals Strong understanding of: TCP/IP Routing & Switching VLANs BGP / OSPF DNS / DHCP Load Balancing Network troubleshooting Automation & Scripting (Preferred) Python PowerShell Bash scripting Security automation SOAR platforms Preferred Certifications Fortinet NSE / FCP Palo Alto PCNSA / PCNSE CCNP Security CISSP CEH CompTIA Security+ Microsoft SC Certifications AWS Security Specialty Education Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, or related field preferred. Soft Skills Strong analytical and troubleshooting skills Ability to work in high-pressure environments Excellent communication and stakeholder management Strong documentation and reporting abilities Proactive mindset with focus on continuous improvement

Location: Poland Job Overview We are looking for an experienced Network Security Engineer to design, implement, monitor, and support enterprise security infrastructure across on-premises, cloud, and hybrid environments. The ideal candidate should possess strong expertise in next-generation firewalls, SIEM platforms, cloud security, Zero Trust architecture, and modern cybersecurity operations. The role requires hands-on experience with technologies such as Fortinet, SonicWall, Palo Alto Networks, SIEM solutions, SASE, SD-WAN, endpoint security, and threat detection platforms. Key Responsibilities Design, deploy, and manage enterprise network security solutions Configure and administer Fortinet, SonicWall, and Palo Alto firewalls Implement and maintain VPNs, IPS/IDS, web filtering, NAT, ACLs, and segmentation policies Monitor security events using SIEM, XDR, and SOC monitoring platforms Investigate security incidents, perform threat analysis, and support incident response activities Manage firewall policies, security rules, and compliance controls Implement Zero Trust Network Access (ZTNA) and identity-based security controls Support cloud security initiatives across AWS, Azure, and hybrid infrastructure Configure and support SD-WAN and Secure Access Service Edge (SASE) solutions Conduct vulnerability assessments and remediation activities Collaborate with infrastructure, cloud, and application teams to secure enterprise environments Maintain security documentation, diagrams, SOPs, and audit records Participate in on-call rotations and critical incident handling GPU East-West and North-South traffic control and security AI networking and security integration expertise Understanding of AI infrastructure design and reference architectures SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Compliance with industry frameworks and standards such as NIST, ISO, etc. Required Skills & Technologies Firewall & Network Security Fortinet FortiGate SonicWall Palo Alto Networks Check Point (preferred) Cisco Firepower / ASA VPN Technologies (IPSec / SSL VPN) IDS/IPS Web Application Firewall (WAF) NAC (Network Access Control) Modern Security Technologies Zero Trust Architecture (ZTA) ZTNA (Zero Trust Network Access) SASE (Secure Access Service Edge) SD-WAN Security SSE (Security Service Edge) CASB (Cloud Access Security Broker) Micro-segmentation Secure Remote Access Solutions SIEM, SOC & Threat Detection Experience with one or more: Splunk QRadar Microsoft Sentinel LogRhythm ArcSight Elastic SIEM Knowledge of: SOC operations Threat hunting Log correlation MITRE ATT&CK framework Incident response Threat intelligence integration Cloud & Infrastructure Security AWS Security Microsoft Azure Security Hybrid cloud networking Cloud firewall management Security Groups / NSGs Identity & Access Management (IAM) Endpoint & Advanced Security EDR/XDR platforms CrowdStrike Microsoft Defender SentinelOne Endpoint hardening DLP (Data Loss Prevention) Email security solutions Networking Fundamentals Strong understanding of: TCP/IP Routing & Switching VLANs BGP / OSPF DNS / DHCP Load Balancing Network troubleshooting Automation & Scripting (Preferred) Python PowerShell Bash scripting Security automation SOAR platforms Preferred Certifications Fortinet NSE / FCP Palo Alto PCNSA / PCNSE CCNP Security CISSP CEH CompTIA Security+ Microsoft SC Certifications AWS Security Specialty Education Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, or related field preferred. Soft Skills Strong analytical and troubleshooting skills Ability to work in high-pressure environments Excellent communication and stakeholder management Strong documentation and reporting abilities Proactive mindset with focus on continuous improvement

Location: Malaysia Job Overview We are seeking a highly experienced Senior Linux Infrastructure Engineer with deep expertise in Linux administration, bare metal infrastructure, enterprise storage, and next-generation AI Factory / GPU infrastructure platforms . This role is focused on designing, deploying, operating, and troubleshooting large-scale Linux-based infrastructure that powers both traditional enterprise workloads and modern AI/ML environments. This is not a DevOps-focused role . We already have a dedicated DevOps team and are looking for an engineer with extensive hands-on experience in Bare Metal as a Service (BMaaS), GPU infrastructure, high-performance storage, data center operations, and enterprise Linux platforms . The ideal candidate will have experience building and managing infrastructure from the hardware layer up, including servers, networking, storage, GPU clusters, and AI-ready platforms. They should be comfortable working with high-performance computing (HPC), AI Factory environments, and large-scale Linux deployments where performance, reliability, and operational excellence are critical. Key Responsibilities & Required Skills Linux & Bare Metal Infrastructure Expert-level Linux administration (Ubuntu required; Red Hat and SUSE preferred) Deep expertise in bare metal server deployment, architecture, provisioning, and lifecycle management Experience operating Bare Metal as a Service (BMaaS) platforms and large-scale infrastructure environments Strong understanding of server hardware, including: BIOS/UEFI RAID controllers Firmware management iLO/iDRAC/IPMI NICs and SmartNICs HBA cards Hardware diagnostics and troubleshooting Experience designing, implementing, and supporting enterprise Linux infrastructure at scale AI Factory & GPU Infrastructure Experience deploying and managing GPU-accelerated infrastructure for AI/ML workloads Understanding of NVIDIA GPU technologies including: A100, H100, H200, B200, or equivalent GPU platforms NVIDIA DGX and OEM GPU servers GPU provisioning and lifecycle management GPU monitoring and performance optimization Knowledge of AI Factory architecture and infrastructure requirements Experience supporting GPU clusters, AI training environments, and high-performance computing (HPC) workloads Understanding of: GPU resource allocation and scheduling Multi-GPU systems GPU networking requirements High-bandwidth, low-latency infrastructure design Familiarity with NVIDIA ecosystem technologies such as: CUDA NCCL GPUDirect Storage NVIDIA Fabric Manager NVIDIA Base Command (preferred) Enterprise Storage & Data Platforms Advanced Linux storage administration: LVM XFS, EXT4 NFS iSCSI Fibre Channel SAN Multipath I/O Strong hands-on experience with Ceph , including: Cluster architecture MON, OSD, MDS RBD, CephFS, RGW Capacity planning Performance tuning Failure recovery Experience with high-performance AI storage platforms such as: WEKA VAST Data Dell PowerScale Pure Storage FlashBlade NetApp Understanding of: NVMe-over-Fabrics (NVMe-oF) RDMA GPUDirect Storage Parallel file systems AI data pipelines Networking & Infrastructure Strong networking knowledge: Bonding VLANs Routing MTU optimization DNS DHCP Experience with high-performance data center networking: 100G/200G/400G Ethernet RoCE RDMA Spine-Leaf architectures Familiarity with NVIDIA Spectrum-X, Mellanox/NVIDIA ConnectX adapters, or equivalent technologies Strong understanding of Layer 2 and Layer 3 infrastructure design and troubleshooting Operations & Reliability Experience with high availability, clustering, and disaster recovery Strong troubleshooting skills across: Linux operating systems Hardware platforms GPU infrastructure Networking Enterprise storage Experience supporting mission-critical production environments Bash and Python scripting for automation and operational efficiency Experience creating operational documentation, runbooks, and infrastructure standards Understanding of AI infrastructure design and reference architectures AI cloud integration for workloads SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Nice to Have Kubernetes infrastructure (especially AI/ML and GPU integration) KVM, VMware, OpenShift Virtualization, or similar virtualization platforms Ansible automation NVIDIA Base Command Manager Slurm or HPC workload schedulers Observability and monitoring platforms (Prometheus, Grafana, OpenTelemetry) Data Center Infrastructure Management (DCIM) tools IPAM solutions AWS, Azure, or hybrid cloud exposure We Are Not Looking For Candidates whose experience is primarily CI/CD pipeline engineering Engineers focused mainly on Terraform, GitOps, or application delivery pipelines Cloud-only administrators with limited bare metal, storage, or hardware experience Professionals whose primary expertise is software development rather than infrastructure engineering Ideal Candidate Someone who has spent years designing, building, and operating enterprise Linux environments, large-scale bare metal infrastructure, storage platforms, and modern AI Factory environments. The ideal candidate understands how to deploy and manage GPU-enabled infrastructure, BMaaS platforms, enterprise storage, and high-performance networking while solving complex operating system, hardware, storage, and AI infrastructure challenges. DevOps experience is a plus, but deep Linux, infrastructure, storage, BMaaS, and AI Factory expertise is the primary requirement.

Location: Singapore Job Overview We are seeking a highly experienced Senior Linux Infrastructure Engineer with deep expertise in Linux administration, bare metal infrastructure, enterprise storage, and next-generation AI Factory / GPU infrastructure platforms . This role is focused on designing, deploying, operating, and troubleshooting large-scale Linux-based infrastructure that powers both traditional enterprise workloads and modern AI/ML environments. This is not a DevOps-focused role . We already have a dedicated DevOps team and are looking for an engineer with extensive hands-on experience in Bare Metal as a Service (BMaaS), GPU infrastructure, high-performance storage, data center operations, and enterprise Linux platforms . The ideal candidate will have experience building and managing infrastructure from the hardware layer up, including servers, networking, storage, GPU clusters, and AI-ready platforms. They should be comfortable working with high-performance computing (HPC), AI Factory environments, and large-scale Linux deployments where performance, reliability, and operational excellence are critical. Key Responsibilities & Required Skills Linux & Bare Metal Infrastructure Expert-level Linux administration (Ubuntu required; Red Hat and SUSE preferred) Deep expertise in bare metal server deployment, architecture, provisioning, and lifecycle management Experience operating Bare Metal as a Service (BMaaS) platforms and large-scale infrastructure environments Strong understanding of server hardware, including: BIOS/UEFI RAID controllers Firmware management iLO/iDRAC/IPMI NICs and SmartNICs HBA cards Hardware diagnostics and troubleshooting Experience designing, implementing, and supporting enterprise Linux infrastructure at scale AI Factory & GPU Infrastructure Experience deploying and managing GPU-accelerated infrastructure for AI/ML workloads Understanding of NVIDIA GPU technologies including: A100, H100, H200, B200, or equivalent GPU platforms NVIDIA DGX and OEM GPU servers GPU provisioning and lifecycle management GPU monitoring and performance optimization Knowledge of AI Factory architecture and infrastructure requirements Experience supporting GPU clusters, AI training environments, and high-performance computing (HPC) workloads Understanding of: GPU resource allocation and scheduling Multi-GPU systems GPU networking requirements High-bandwidth, low-latency infrastructure design Familiarity with NVIDIA ecosystem technologies such as: CUDA NCCL GPUDirect Storage NVIDIA Fabric Manager NVIDIA Base Command (preferred) Enterprise Storage & Data Platforms Advanced Linux storage administration: LVM XFS, EXT4 NFS iSCSI Fibre Channel SAN Multipath I/O Strong hands-on experience with Ceph , including: Cluster architecture MON, OSD, MDS RBD, CephFS, RGW Capacity planning Performance tuning Failure recovery Experience with high-performance AI storage platforms such as: WEKA VAST Data Dell PowerScale Pure Storage FlashBlade NetApp Understanding of: NVMe-over-Fabrics (NVMe-oF) RDMA GPUDirect Storage Parallel file systems AI data pipelines Networking & Infrastructure Strong networking knowledge: Bonding VLANs Routing MTU optimization DNS DHCP Experience with high-performance data center networking: 100G/200G/400G Ethernet RoCE RDMA Spine-Leaf architectures Familiarity with NVIDIA Spectrum-X, Mellanox/NVIDIA ConnectX adapters, or equivalent technologies Strong understanding of Layer 2 and Layer 3 infrastructure design and troubleshooting Operations & Reliability Experience with high availability, clustering, and disaster recovery Strong troubleshooting skills across: Linux operating systems Hardware platforms GPU infrastructure Networking Enterprise storage Experience supporting mission-critical production environments Bash and Python scripting for automation and operational efficiency Experience creating operational documentation, runbooks, and infrastructure standards Understanding of AI infrastructure design and reference architectures AI cloud integration for workloads SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Nice to Have Kubernetes infrastructure (especially AI/ML and GPU integration) KVM, VMware, OpenShift Virtualization, or similar virtualization platforms Ansible automation NVIDIA Base Command Manager Slurm or HPC workload schedulers Observability and monitoring platforms (Prometheus, Grafana, OpenTelemetry) Data Center Infrastructure Management (DCIM) tools IPAM solutions AWS, Azure, or hybrid cloud exposure We Are Not Looking For Candidates whose experience is primarily CI/CD pipeline engineering Engineers focused mainly on Terraform, GitOps, or application delivery pipelines Cloud-only administrators with limited bare metal, storage, or hardware experience Professionals whose primary expertise is software development rather than infrastructure engineering Ideal Candidate Someone who has spent years designing, building, and operating enterprise Linux environments, large-scale bare metal infrastructure, storage platforms, and modern AI Factory environments. The ideal candidate understands how to deploy and manage GPU-enabled infrastructure, BMaaS platforms, enterprise storage, and high-performance networking while solving complex operating system, hardware, storage, and AI infrastructure challenges. DevOps experience is a plus, but deep Linux, infrastructure, storage, BMaaS, and AI Factory expertise is the primary requirement.

Location: Serbia Job Overview We are seeking a highly experienced Senior Linux Infrastructure Engineer with deep expertise in Linux administration, bare metal infrastructure, enterprise storage, and next-generation AI Factory / GPU infrastructure platforms . This role is focused on designing, deploying, operating, and troubleshooting large-scale Linux-based infrastructure that powers both traditional enterprise workloads and modern AI/ML environments. This is not a DevOps-focused role . We already have a dedicated DevOps team and are looking for an engineer with extensive hands-on experience in Bare Metal as a Service (BMaaS), GPU infrastructure, high-performance storage, data center operations, and enterprise Linux platforms . The ideal candidate will have experience building and managing infrastructure from the hardware layer up, including servers, networking, storage, GPU clusters, and AI-ready platforms. They should be comfortable working with high-performance computing (HPC), AI Factory environments, and large-scale Linux deployments where performance, reliability, and operational excellence are critical. Key Responsibilities & Required Skills Linux & Bare Metal Infrastructure Expert-level Linux administration (Ubuntu required; Red Hat and SUSE preferred) Deep expertise in bare metal server deployment, architecture, provisioning, and lifecycle management Experience operating Bare Metal as a Service (BMaaS) platforms and large-scale infrastructure environments Strong understanding of server hardware, including: BIOS/UEFI RAID controllers Firmware management iLO/iDRAC/IPMI NICs and SmartNICs HBA cards Hardware diagnostics and troubleshooting Experience designing, implementing, and supporting enterprise Linux infrastructure at scale AI Factory & GPU Infrastructure Experience deploying and managing GPU-accelerated infrastructure for AI/ML workloads Understanding of NVIDIA GPU technologies including: A100, H100, H200, B200, or equivalent GPU platforms NVIDIA DGX and OEM GPU servers GPU provisioning and lifecycle management GPU monitoring and performance optimization Knowledge of AI Factory architecture and infrastructure requirements Experience supporting GPU clusters, AI training environments, and high-performance computing (HPC) workloads Understanding of: GPU resource allocation and scheduling Multi-GPU systems GPU networking requirements High-bandwidth, low-latency infrastructure design Familiarity with NVIDIA ecosystem technologies such as: CUDA NCCL GPUDirect Storage NVIDIA Fabric Manager NVIDIA Base Command (preferred) Enterprise Storage & Data Platforms Advanced Linux storage administration: LVM XFS, EXT4 NFS iSCSI Fibre Channel SAN Multipath I/O Strong hands-on experience with Ceph , including: Cluster architecture MON, OSD, MDS RBD, CephFS, RGW Capacity planning Performance tuning Failure recovery Experience with high-performance AI storage platforms such as: WEKA VAST Data Dell PowerScale Pure Storage FlashBlade NetApp Understanding of: NVMe-over-Fabrics (NVMe-oF) RDMA GPUDirect Storage Parallel file systems AI data pipelines Networking & Infrastructure Strong networking knowledge: Bonding VLANs Routing MTU optimization DNS DHCP Experience with high-performance data center networking: 100G/200G/400G Ethernet RoCE RDMA Spine-Leaf architectures Familiarity with NVIDIA Spectrum-X, Mellanox/NVIDIA ConnectX adapters, or equivalent technologies Strong understanding of Layer 2 and Layer 3 infrastructure design and troubleshooting Operations & Reliability Experience with high availability, clustering, and disaster recovery Strong troubleshooting skills across: Linux operating systems Hardware platforms GPU infrastructure Networking Enterprise storage Experience supporting mission-critical production environments Bash and Python scripting for automation and operational efficiency Experience creating operational documentation, runbooks, and infrastructure standards Understanding of AI infrastructure design and reference architectures AI cloud integration for workloads SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Nice to Have Kubernetes infrastructure (especially AI/ML and GPU integration) KVM, VMware, OpenShift Virtualization, or similar virtualization platforms Ansible automation NVIDIA Base Command Manager Slurm or HPC workload schedulers Observability and monitoring platforms (Prometheus, Grafana, OpenTelemetry) Data Center Infrastructure Management (DCIM) tools IPAM solutions AWS, Azure, or hybrid cloud exposure We Are Not Looking For Candidates whose experience is primarily CI/CD pipeline engineering Engineers focused mainly on Terraform, GitOps, or application delivery pipelines Cloud-only administrators with limited bare metal, storage, or hardware experience Professionals whose primary expertise is software development rather than infrastructure engineering Ideal Candidate Someone who has spent years designing, building, and operating enterprise Linux environments, large-scale bare metal infrastructure, storage platforms, and modern AI Factory environments. The ideal candidate understands how to deploy and manage GPU-enabled infrastructure, BMaaS platforms, enterprise storage, and high-performance networking while solving complex operating system, hardware, storage, and AI infrastructure challenges. DevOps experience is a plus, but deep Linux, infrastructure, storage, BMaaS, and AI Factory expertise is the primary requirement.

Location: Poland Job Overview We are seeking a highly experienced Senior Linux Infrastructure Engineer with deep expertise in Linux administration, bare metal infrastructure, enterprise storage, and next-generation AI Factory / GPU infrastructure platforms . This role is focused on designing, deploying, operating, and troubleshooting large-scale Linux-based infrastructure that powers both traditional enterprise workloads and modern AI/ML environments. This is not a DevOps-focused role . We already have a dedicated DevOps team and are looking for an engineer with extensive hands-on experience in Bare Metal as a Service (BMaaS), GPU infrastructure, high-performance storage, data center operations, and enterprise Linux platforms . The ideal candidate will have experience building and managing infrastructure from the hardware layer up, including servers, networking, storage, GPU clusters, and AI-ready platforms. They should be comfortable working with high-performance computing (HPC), AI Factory environments, and large-scale Linux deployments where performance, reliability, and operational excellence are critical. Key Responsibilities & Required Skills Linux & Bare Metal Infrastructure Expert-level Linux administration (Ubuntu required; Red Hat and SUSE preferred) Deep expertise in bare metal server deployment, architecture, provisioning, and lifecycle management Experience operating Bare Metal as a Service (BMaaS) platforms and large-scale infrastructure environments Strong understanding of server hardware, including: BIOS/UEFI RAID controllers Firmware management iLO/iDRAC/IPMI NICs and SmartNICs HBA cards Hardware diagnostics and troubleshooting Experience designing, implementing, and supporting enterprise Linux infrastructure at scale AI Factory & GPU Infrastructure Experience deploying and managing GPU-accelerated infrastructure for AI/ML workloads Understanding of NVIDIA GPU technologies including: A100, H100, H200, B200, or equivalent GPU platforms NVIDIA DGX and OEM GPU servers GPU provisioning and lifecycle management GPU monitoring and performance optimization Knowledge of AI Factory architecture and infrastructure requirements Experience supporting GPU clusters, AI training environments, and high-performance computing (HPC) workloads Understanding of: GPU resource allocation and scheduling Multi-GPU systems GPU networking requirements High-bandwidth, low-latency infrastructure design Familiarity with NVIDIA ecosystem technologies such as: CUDA NCCL GPUDirect Storage NVIDIA Fabric Manager NVIDIA Base Command (preferred) Enterprise Storage & Data Platforms Advanced Linux storage administration: LVM XFS, EXT4 NFS iSCSI Fibre Channel SAN Multipath I/O Strong hands-on experience with Ceph , including: Cluster architecture MON, OSD, MDS RBD, CephFS, RGW Capacity planning Performance tuning Failure recovery Experience with high-performance AI storage platforms such as: WEKA VAST Data Dell PowerScale Pure Storage FlashBlade NetApp Understanding of: NVMe-over-Fabrics (NVMe-oF) RDMA GPUDirect Storage Parallel file systems AI data pipelines Networking & Infrastructure Strong networking knowledge: Bonding VLANs Routing MTU optimization DNS DHCP Experience with high-performance data center networking: 100G/200G/400G Ethernet RoCE RDMA Spine-Leaf architectures Familiarity with NVIDIA Spectrum-X, Mellanox/NVIDIA ConnectX adapters, or equivalent technologies Strong understanding of Layer 2 and Layer 3 infrastructure design and troubleshooting Operations & Reliability Experience with high availability, clustering, and disaster recovery Strong troubleshooting skills across: Linux operating systems Hardware platforms GPU infrastructure Networking Enterprise storage Experience supporting mission-critical production environments Bash and Python scripting for automation and operational efficiency Experience creating operational documentation, runbooks, and infrastructure standards Understanding of AI infrastructure design and reference architectures AI cloud integration for workloads SOP and runbook development and maintenance Incident, problem, and capacity management Business continuity and disaster recovery planning for AI workloads Proactive risk identification and mitigation to avoid business impact Nice to Have Kubernetes infrastructure (especially AI/ML and GPU integration) KVM, VMware, OpenShift Virtualization, or similar virtualization platforms Ansible automation NVIDIA Base Command Manager Slurm or HPC workload schedulers Observability and monitoring platforms (Prometheus, Grafana, OpenTelemetry) Data Center Infrastructure Management (DCIM) tools IPAM solutions AWS, Azure, or hybrid cloud exposure We Are Not Looking For Candidates whose experience is primarily CI/CD pipeline engineering Engineers focused mainly on Terraform, GitOps, or application delivery pipelines Cloud-only administrators with limited bare metal, storage, or hardware experience Professionals whose primary expertise is software development rather than infrastructure engineering Ideal Candidate Someone who has spent years designing, building, and operating enterprise Linux environments, large-scale bare metal infrastructure, storage platforms, and modern AI Factory environments. The ideal candidate understands how to deploy and manage GPU-enabled infrastructure, BMaaS platforms, enterprise storage, and high-performance networking while solving complex operating system, hardware, storage, and AI infrastructure challenges. DevOps experience is a plus, but deep Linux, infrastructure, storage, BMaaS, and AI Factory expertise is the primary requirement.

Location: United States Workplace: Remote Recognized on the 2025 Forbes Cloud 100 list https://www.forbes.com/companies/clickhouse/?list=cloud100, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 4,000 customers and $250M ARR https://clickhouse.com/blog/clickhouse-tops-250m-arr-and-4000-customers, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.   The company's sustained, accelerating momentum was recently validated by a $400M Series D financing round https://clickhouse.com/blog/clickhouse-raises-400-million-series-d-acquires-langfuse-launches-postgres. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.   We're on a mission to transform how companies use data. Come be a part of our journey! We're looking for a Senior Revenue Accountant to join our revenue accounting team. You will report to the Director of Order to Cash and Revenue Accounting and be responsible for executing the month-end close cycle for revenue recognition, including reconciliations for revenue and deferred revenue, reviewing customer contracts, and preparing financial reporting metrics such as RPO. You'll work cross-functionally with AR & Billing, Legal, Sales Operations, FP&A, and Data teams to build scalable, automated revenue processes. YOU WILL - Own the end-to-end monthly revenue close, preparing journal entries, reconciliations, and flux analyses for revenue, deferred revenue, and contract asset balances. - Prepare the deferred revenue waterfall and financial reporting metrics. - Reconcile consumption data to billing and revenue; use SQL/data queries and AI tools to assist and automate the work. - Review customer contracts and order forms under ASC 606, and prepare accounting checklist for complex or non-standard deals. - Prepare estimate calculations, including the standalone selling price (SSP) analyses. - Support new product introductions (NPI), new pricing models, SKU launches, and system upgrades or implementations. - Support external audits and manage PBC requests related to revenue. - Collaborate cross-functionally with AR & Billing, Legal, Sales Operations, FP&A, and Data teams to improve the quote-to-revenue workflow. YOU BRING - 3+ years of progressive accounting experience with a focus on revenue accounting, ideally at a SaaS or consumption-based technology company. - Strong working knowledge of ASC 606, including contract review, SSP, and revenue disclosures (deferred revenue, RPO). - Experience with NetSuite, Stripe, and Salesforce, and familiarity with the integrations and data flows among these systems; experience with cloud marketplace billing (AWS, GCP, Azure) is a plus. - Comfort working with large data sets; SQL or similar query skills, and an interest in using AI and automation to streamline processes. - Strong analytical and problem-solving skills, with the ability to interpret complex contracts and data sets. - A quick learner with excellent attention to detail, organization, and communication skills; able to collaborate cross-functionally and explain revenue matters clearly. - CPA (or equivalent) and/or Big Four public accounting experience preferred. - Experience supporting audits, internal controls, and SOX readiness preferred. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new eligible team member who joins our company receives equity. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Задачи: — Установка и администрирование виртуальных машин. — Развёртывание и сопровождение Kubernetes-кластера. — Разработка и поддержка CI/CD пайплайнов (GitLab). — Создание Helm-чартов и Ansible-плейбуков. — Мониторинг инфраструктуры (Zabbix, Prometheus, Grafana). — Ведение документации в Wiki. — Деплой приложений (сервисы, контейнеры). — Взаимодействие с разработчиками. — Диагностика и устранение проблем. — Предупреждение сбоев и обеспечение стабильности сервисов. Требования: — Опыт администрирования Linux (Ubuntu) от 3 лет. — Опыт с Kubernetes (или OpenShift) от 2–3 лет. — Знание Docker и Helm. — Опыт с VMware, AWS, GCP. — Навыки настройки CI/CD (GitLab). — Владение Git. — Опыт взаимодействия с разработчиками. — Знание PostgreSQL, Nginx, RabbitMQ, Zabbix. — Автоматизация через Ansible и скрипты (bash). — Анализ логов и работа с ними в Linux. Условия: — Работа в команде профессионалов, наставничество. — Динамичный бизнес с международными проектами. — Практика и развитие компетенций, индивидуальный план развития. — Удалённая работа из любой точки мира. — Официальное оформление по ТК РФ, возможна релокация в Сербию после испытательного срока. — Конкурентная заработная плата с возможностью роста. — Стабильная оплата с учётом всех выплат. — Гибкий график работы. — ДМС с первого рабочего дня, включая стоматологию.