Devops & SysOps Architect
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Before you apply
LocationCairo, Cairo Governorate, Egypt
Typefull-time
SeniorityLead
Experience10+ yrs
DepartmentSoftware Development
Company size51–200 people
PostedApr 26, 2026 · 6mo ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
10+ years in platform/infrastructure engineering, with at least 2 years in architect-level role
Proven hands-on experience operating Kubernetes at scale in production (multi-cluster, multi-tenant)
Significant Linux systems administration experience — kernel, networking, storage at a low level
HPC and/or GPU infrastructure experience — physical GPU servers, NCCL, InfiniBand, or high-speed fabrics
Demonstrable presales or client-facing experience
IaC experience: Terraform and/or Ansible in production environments
Strong understanding of GitOps and CI/CD pipelines in enterprise settings
Experience with NVIDIA GPU Operator, MIG partitioning, Run:AI, or equivalent GPU scheduling tooling
Knowledge of distributed AI training infrastructure (PyTorch DDP, Horovod, DeepSpeed) from an infrastructure perspective
Familiarity with NVIDIA Triton Inference Server or TensorRT deployment pipelines
Experience with Weka, Ceph, or GPUDirect Storage in HPC/AI environments
Hands-on experience with Vault, External Secrets, and zero-trust network architectures
Exposure to bare-metal provisioning and HPC cluster management (Slurm, PBS, or equivalent)
CKA / CKS certification
RHCE / RHCA certification
AWS Solutions Architect / Azure Solutions Architect Expert certification
HashiCorp Terraform Associate or Vault Associate certification
NVIDIA DLI certifications (GPU computing, AI infrastructure)
Skills
Kubernetes
RKE2
EKS
AKS
GPU
NVIDIA H100
NVIDIA A100
NVIDIA B200
Istio
Cilium
Longhorn
Ceph
ArgoCD
Fleet
Azure DevOps
Jenkins
Terraform
Ansible
Run:AI
NVIDIA Triton Inference Server
TensorRT
CUDA
cuDNN
NCCL
InfiniBand
RoCE
GPUDirect RDMA
GPUDirect Storage
Prometheus
Thanos
Loki
Fluent Bit
DCGM Exporter
NVIDIA Nsight Systems
HashiCorp Vault
External Secrets Operator
Weka
Slurm
PBS
Python
PyTorch DDP
Horovod
DeepSpeed
Linux
Benefits
Competitive compensation package
PTO
Full medical and dental coverage
Opportunity to travel and work onsite with u.s. customers
In house technical and english training programs
Dedicated learning time
Interest free loans
Flexible work schedules
Events
Sponsored lunch
Game area
Rooftop hangout
About the role
We are seeking an exceptional Senior Lead who combines deep hands-on SysOps/HPC expertise with the strategic vision of a solution architect. This is a rare dual-track role: you operate at the intersection of elite technical execution and client-facing presales, designing and running mission-critical GPU, HPC, and Kubernetes platforms while simultaneously co-creating opportunity with our commercial teams.
This role carries both SysOps, HPC depth and DevOps. You are expected to spend at least 60% of your time on implementation and technical execution
What You Will Do
Presales & Business Development
• Partner with sales and solution teams to identify and qualify new opportunities
• Lead or support technical presales activities: discovery workshops, RFP responses, architecture presentations
• Build and deliver proof-of-concepts (POCs) that demonstrate platform capabilities to prospective clients
• Prepare high-quality technical materials
• Act as a trusted technical advisor during client conversations, proposing solutions aligned to business goals
In-Account Delivery — SysOps & DevOps Execution
• Operate directly within client accounts as a senior SysOps/DevOps engineer
• Run, troubleshoot, and optimize production-grade Kubernetes clusters and GPU/HPC environments hands-on
• Own Linux system administration at a deep level: kernel tuning, storage, networking, performance profiling
• Implement and maintain IaC pipelines, GitOps workflows, and CI/CD systems
• Serve as the senior escalation point for complex operational incidents within accounts
Architecture & Solution Design
• Design end-to-end platform architectures spanning cloud, hybrid, and on-premises HPC environments
• Define workload isolation models, networking architectures, and storage strategies for multi-tenant platforms
• Recommend and validate technology choices aligned to client scale, budget, and team maturity
• Produce architecture decision records (ADRs), solution blueprints, and technical runbooks
Technical Competencies & Requirements
1. Architecture & System Design
• Design production-grade multi-cluster Kubernetes platforms:
◦ RKE2, EKS (AWS), AKS (Azure) at enterprise scale
◦ GPU-aware clusters: NVIDIA H100 / A100 / B200 node pools
◦ Hybrid cloud + on-premises HPC infrastructure
• Define and document:
◦ Workload isolation: namespaces, MIG partitioning, multi-tenancy models
◦ Networking: BGP peering, Ingress controllers, service mesh (Istio / Cilium)
◦ Storage: Longhorn, Ceph, distributed and high-throughput file systems
2. Platform Engineering & GitOps Strategy
• Define and enforce platform standards across the delivery lifecycle
• GitOps tooling: ArgoCD, Fleet — declarative cluster management
• CI/CD pipelines: Azure DevOps, Jenkins — build, test, promote
• Infrastructure as Code: Terraform (modules, remote state, workspaces), Ansible
• Standardize cluster bootstrapping, app deployment lifecycle, environment promotion (Dev → QA → Prod)
3. AI / GPU Infrastructure Architecture (Priority Competency)
• Design and operate GPU compute platforms at scale:
◦ GPU Operator deployment and lifecycle management
◦ MIG (Multi-Instance GPU) partitioning for multi-tenant workloads
◦ Advanced scheduling: Run:AI, Kubernetes-native GPU scheduling (device plugins)
• Understand AI workload classes and their infrastructure implications:
◦ Distributed training workloads (data/model/pipeline parallelism)
◦ Inference pipelines — NVIDIA Triton Inference Server, TensorRT optimization
• Align infrastructure to the full AI stack:
◦ CUDA stack, cuDNN, NCCL collective communication libraries
◦ High-speed networking: InfiniBand (HDR/NDR), RoCE for RDMA
◦ GPUDirect RDMA / GPUDirect Storage for low-latency data paths
4. Observability & Reliability Engineering
• Define and implement full-stack observability:
◦ Metrics: Prometheus, Thanos (long-term retention, multi-cluster)
◦ Logs: Loki, Fluent Bit
◦ GPU telemetry: DCGM Exporter, NVIDIA Nsight Systems
• Build operational frameworks:
◦ SLO / SLA definitions and error budget tracking
◦ Alerting strategy — noise reduction, severity routing
◦ Incident response playbooks and on-call runbooks
5. Security & Multi-Tenancy Architecture
• Design zero-trust security postures for multi-tenant platforms
• Secret management: HashiCorp Vault, External Secrets Operator
• Identity and access: IAM, RBAC, SSO/OIDC integration
• Network isolation: NetworkPolicy, micro-segmentation, mTLS
• Secure GPU sharing: MIG isolation, VGPU licensing, tenant boundary enforcement
6. HPC, Data & Storage Architecture (Priority Competency)
• Understand the high-performance storage for AI/HPC workloads:
◦ GPUDirect Storage — bypassing CPU for GPU-native I/O
◦ Distributed file systems: Weka (high-throughput NFS/S3), Ceph (scalable object/block)
◦ Storage tiering, caching strategies, and data lifecycle management
• Size and validate storage architectures against workload I/O profiles
7. Operational Leadership & Linux Systems
• Lead incident response and root cause analysis (RCA) for critical production issues
• Define upgrade strategies, change management procedures, and disaster recovery plans
• Write and maintain runbooks, operational playbooks, and knowledge base content
• Integrate organizational processes, compliance requirements, and security policies into operational frameworks
• Deep Linux expertise:
◦ Kernel tuning (CPU governor, NUMA, IRQ affinity, hugepages)
◦ Storage I/O scheduling, NVMe optimization
◦ Network stack tuning for RDMA / InfiniBand
◦ System performance profiling and bottleneck analysis
Candidate Profile — Who You Are
• you are comfortable running production systems.
• You have stronger SysOps and HPC depth than DevOps breadth, and you embrace that identity
• You can shift fluidly between running a live incident, presenting an architecture to a CTO, and reviewing a POC demo environment
• You communicate technical complexity clearly — to engineers and to C-level stakeholders
• You understand why specific tooling choices matter (not just how to configure them) and can articulate trade-offs in presales conversations
• You are comfortable owning outcomes across both commercial (presales) and delivery (operations) dimensions
• You thrive in ambiguity and can scope both short POCs and long-horizon platform programs
Requirements
Required
• 10+ years in platform/infrastructure engineering, with at least 2 years in architect-level role
• Proven hands-on experience operating Kubernetes at scale in production (multi-cluster, multi-tenant)
• Significant Linux systems administration experience — kernel, networking, storage at a low level
• HPC and/or GPU infrastructure experience — physical GPU servers, NCCL, InfiniBand, or high-speed fabrics
• Demonstrable presales or client-facing experience
• IaC experience: Terraform and/or Ansible in production environments
• Strong understanding of GitOps and CI/CD pipelines in enterprise settings
Strongly Preferred
• Experience with NVIDIA GPU Operator, MIG partitioning, Run:AI, or equivalent GPU scheduling tooling
• Knowledge of distributed AI training infrastructure (PyTorch DDP, Horovod, DeepSpeed) from an infrastructure perspective
• Familiarity with NVIDIA Triton Inference Server or TensorRT deployment pipelines
• Experience with Weka, Ceph, or GPUDirect Storage in HPC/AI environments
• Hands-on experience with Vault, External Secrets, and zero-trust network architectures
• Exposure to bare-metal provisioning and HPC cluster management (Slurm, PBS, or equivalent)
Certifications (Advantageous)
• CKA / CKS (Certified Kubernetes Administrator / Security Specialist)
• RHCE / RHCA (Red Hat Certified Engineer / Architect)
• AWS Solutions Architect / Azure Solutions Architect Expert
• HashiCorp Terraform Associate or Vault Associate
• NVIDIA DLI certifications (GPU computing, AI infrastructure)
Benefits
•
Why Integrant?
•
Competitive compensation package
•
PTO, full medical and dental coverage, etc.
•
Opportunity to travel and work onsite with U.S. customers
•
In-house Technical and English training programs
•
Dedicated learning time (check out our 4Plus1 Program) [link]
•
Interest free loans
•
Flexible work schedules
•
Perks: events, sponsored lunch, game area, rooftop hangout + more!