ai infrastructure architect

Acenet consulting

<div><div>Experience: 10 to 15 years
 
Location: Abu Dhabi
 
Job code: 101484
 
Posted on: Apr 17, 2026 
</div> 
About Us: 
AceNet Consulting is a fast-growing global business and technology consulting firm leveraging a consultative approach, deep domain expertise and strong technology capabilities across business transformation, IT strategy &amp; architecture, digital transformation, data engineering &amp; analytics, AI/ML, cloud &amp; infrastructure, enterprise applications and emerging technologies to deliver value to our global clients. AceNet&rsquo;s marquee clients include Tier-1 and Tier-2 banking &amp; financial services, asset &amp; wealth management, healthcare, consumer retail, eCommerce &amp; logistics, engineering, government &amp; public sectors, consulting and technology firms. With presence across Abu Dhabi UAE, Texas USA and India (Bangalore, Gurgaon &amp; Pune), AceNet brings strong consulting and delivery capabilities across project staffing, managed services, outsourcing and offshoring.
Job Summary: 
We are seeking a Senior Azure AI Infrastructure Architect to lead the design, governance, security, and operationalization of AI infrastructure on Microsoft Azure. Operating within a centralized Cloud Center of Excellence (CoE), this role will act as the enterprise platform authority for Azure AI services. The architect will partner closely with application teams, data scientists, security, networking, and operations teams to provision, secure, optimize, and transition AI solutions into production at scale. This is a senior-level role requiring deep Azure expertise, strong governance orientation, and the ability to enable AI innovation within a controlled, secure enterprise framework.
<div>Key Responsibilities: 
<ul><li>Design and maintain enterprise-grade Azure AI resources.</li><li>Architect infrastructure for Azure OpenAI, Azure Machine Learning, Azure AI Services, GPU-based compute environments, and AKS for AI workloads.</li><li>Define subscription strategy, resource group structure, tagging standards, and naming conventions aligned with CoE governance.</li><li>Design secure networking architectures including VNET segmentation, Private Endpoints, Firewall, and NSGs.</li><li>Continuously monitor and improve security posture using Microsoft Defender for Cloud and related tools.</li><li>Implement least-privilege RBAC models and ensure secure identity integration.</li><li>Enforce governance controls using Azure Policy and Management Groups.</li><li>Review AI solution architectures and participate in architecture review boards.</li><li>Monitor and optimize AI workload costs using Azure Cost Management and FinOps practices.</li><li>Implement Infrastructure as Code using Terraform (preferred), Bicep, or ARM templates.</li><li>Support CI/CD pipelines and controlled change and release management processes.</li><li>Develop operational runbooks and ensure smooth transition of AI services to operations teams.</li><li>Act as the primary AI infrastructure advisor within the Cloud CoE and guide stakeholders on best practices.</li></ul></div>
<div>Required Skills &amp; Experience: 
<ul><li>Deep hands-on expertise in Microsoft Azure and Azure AI services.</li><li>Strong experience designing AI landing zones and enterprise cloud architectures.</li><li>Advanced knowledge of Azure networking (VNETs, Private Link, Hybrid connectivity).</li><li>Strong expertise in Azure RBAC, Entra ID, Managed Identities, Azure Policy, and Key Vault.</li><li>Experience with Microsoft Defender for Cloud and enterprise security monitoring.</li><li>Hands-on experience with Infrastructure as Code and CI/CD pipelines.</li><li>Strong FinOps mindset and experience managing Azure cost optimization.</li><li>10+ years in IT infrastructure/cloud architecture.</li><li>5+ years of hands-on Azure architecture experience.</li><li>Experience operating within a centralized Cloud CoE model.</li><li>Preferred Certifications:</li><li>Microsoft Certified: Azure Solutions Architect Expert</li><li>Microsoft Certified: Azure Security Engineer Associate</li><li>Microsoft Certified: Azure AI Engineer Associate</li><li>Microsoft Certified: Azure Administrator Associate</li></ul></div>
<div>Why Join Us: 
<ul><li>Opportunities to work on transformative projects, cutting-edge technology and innovative solutions with leading global firms across industry sectors.</li><li>Continuous investment in employee growth and professional development with a strong focus on up &amp; re-skilling.</li><li>Competitive compensation &amp; benefits, ESOPs and international assignments.</li><li>Supportive environment with healthy work-life balance and a focus on employee well-being.</li><li>Open culture that values diverse perspectives, encourages transparent communication and rewards contributions.</li></ul></div>
How to Apply: 
If you are interested in joining our team and meet the qualifications listed above, please apply and submit your resume highlighting why you are the ideal candidate for this position.</div>

Senior Azure AI Infrastructure Architect

NVIDIA

<div>NVIDIA is looking for a Senior Solutions Architect, Customer Success to join its NVIDIA Infrastructure Specialist Team. Academic and commercial organizations around the world are using NVIDIA products to redefine deep learning and data analytics, and to power next-generation data centers. Join the team building and advising on many of the largest and fastest AI/HPC systems in the world!
We are looking for someone who blends deep technical expertise with a consultative, collaborative approach. This role will engage directly with customers, partners, and multi-functional internal teams to assess infrastructure needs, architect scalable solutions, and guide the implementation of large-scale networking and AI infrastructure projects. The scope spans networking, system design, and automation&mdash;serving as a trusted strategic advisor and the technical face of NVIDIA to key accounts.
What You&rsquo;ll Be Doing:<ul><li>
Serve as a senior technical authority and trusted consultant on NVIDIA technologies, contributing to architecture reviews, guiding infrastructure decisions at scale, and providing strategic recommendations aligned with each customer&rsquo;s business objectives.</li><li>
Establish and refine monitoring and optimization methodologies using analytics, telemetry, and automation to proactively detect bottlenecks, improve infrastructure resiliency, and drive continuous operational maturity.</li><li>
Lead and advise on the analysis, optimization, and performance tuning of complex GPU-accelerated systems and AI workloads, ensuring high availability and efficiency across customer data centers.</li><li>
Facilitate post-deployment reviews, incident retrospectives, and strategy sessions to shape the customer experience and deliver actionable insights into NVIDIA&rsquo;s infrastructure roadmap.</li><li>
Own and lead complex technical projects end-to-end&mdash;from initial discovery and solution design through implementation, knowledge transfer, and continuous improvement&mdash;ensuring alignment to SLAs and proactive mitigation of technical risks.</li><li>
Support business growth by identifying AI infrastructure opportunities in cloud and enterprise environments, crafting compelling technical proposals, and driving initiatives that showcase NVIDIA&rsquo;s leadership in this space.</li></ul> 
What We Need to See:<ul><li>
Education &amp; Experience: BS/MS/PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields, with 10+ years of professional experience in large-scale data center service operations with a focus on infrastructure.</li><li>
NVIDIA GPU Expertise: Demonstrated hands-on experience deploying, configuring, and optimizing NVIDIA GPU-accelerated infrastructure, including driver and firmware management, CUDA toolkit integration, and GPU workload profiling and fix.</li><li>
Customer Engagement: Track record of building long-term customer relationships and driving adoption through consultative engagement.</li><li>
Analytical &amp; Problem-Solving Skills: Strong analytical and decision-making capabilities, with a demonstrable ability to identify root causes, drive continuous improvement, and deliver resilient technical solutions.</li><li>
System &amp; Infrastructure Proficiency: Expertise in end-to-end data center architecture, spanning operating systems, Linux kernel drivers, GPU and NIC hardware, high-speed networking (InfiniBand, Ethernet, RDMA), and storage systems (Lustre, GPFS, NFS).</li><li>
Leadership &amp; Communication: Good communication, time management, and organizational skills, with the ability to lead complex multi-functional projects, guide technical teams, and present to executive partners.</li><li>
Travel: Willingness to travel up to 25% for customer engagements.</li></ul> 
Ways to Stand Out from the Crowd:<ul><li>
Experience with Kubernetes for container orchestration, resource scheduling, and integration with GPU-accelerated workloads.</li><li>
Familiarity with observability stacks (Grafana, Prometheus, Loki) for monitoring, alerting, and building fault-tolerant systems.</li><li>
Experience with multi-tenant GPU cluster management and workload scheduling frameworks.</li><li>
Experience with NVIDIA Base Command Manager (BCM) for provisioning, managing, and monitoring GPU clusters at scale.</li><li>
Background with RDMA-based fabrics (InfiniBand or RoCE) in HPC or AI environments as well as knowledge of CI/CD pipelines, Infrastructure-as-Code (Terraform, Ansible), and GitOps workflows for infrastructure automation.</li></ul></div>

Senior Solutions Architect, Customer Success

<div>NVIDIA is looking for a Senior Cloud Infrastructure and DevOps Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial organizations around the world are using NVIDIA products to redefine deep learning and data analytics, and to power next-generation data centers. Join the team building and advising on many of the largest and fastest AI/HPC systems in the world!
We are looking for someone who combines deep technical expertise with strong consulting and communication skills. This role will engage directly with customers, partners, and multi-functional teams to assess, architect, and guide the implementation of large-scale infrastructure projects. The scope spans system architecture, Kubernetes-based platforms, and automation&mdash;serving as both a trusted advisor and a hands-on technical leader.
What You&rsquo;ll Be Doing:<ul><li>
Advise on and help maintain large-scale computational and AI infrastructure, including monitoring, logging, and workload orchestration (Kubernetes and Linux job schedulers).</li><li>
Provide consultative guidance and perform hands-on solving across the full stack&mdash;from bare metal and operating system, through the software stack, container platform, networking, and storage.</li><li>
Assess customer environments and recommend optimized, production-ready Kubernetes-based container platforms integrated with enterprise-grade networking and storage solutions.</li><li>
Serve as a key technical resource: develop, refine, and document standard methodologies and operational guidelines to be shared with internal teams and customer partners.</li><li>
Support Research &amp; Development activities and engage in POCs/POVs to validate new features, architectures, and upgrade approaches.</li><li>
Create and deliver high-quality documentation, including runbooks, onboarding materials, and best-practice guides for customers and internal teams.</li><li>
Act as the technical leader for assigned customer accounts, providing strategic guidance on DevOps and platform architecture and influencing long-term infrastructure and operations decisions.</li></ul>
What We Need to See:<ul><li>
Education &amp; Experience: BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields (or equivalent experience), with 8+ years of professional experience in leading scalable cloud environments and automation engineering roles.</li><li>
Cloud &amp; HPC Expertise: Shown understanding of networking fundamentals, data center architectures, and hands-on experience leading HPC/AI clusters, including deployment, optimization, and solving.</li><li>
NVIDIA GPU Expertise: Validated hands-on experience deploying, configuring, and optimizing NVIDIA GPU-accelerated infrastructure, including driver management, CUDA toolkit integration, and GPU workload profiling.</li><li>
Kubernetes &amp; AI/ML Workloads: Extensive experience with Kubernetes for container orchestration, resource scheduling, scaling, and integration with GPU-accelerated and HPC environments.</li><li>
Hardware &amp; Software Knowledge: Strong familiarity with HPC and AI technologies (CPUs, GPUs, high-speed interconnects) and supporting software stacks.</li><li>
Linux &amp; Storage Systems: Deep knowledge of Linux (RedHat, Ubuntu), OS-level security, and protocols. Experience with storage solutions such as Lustre, GPFS, ZFS, XFS, and emerging Kubernetes storage technologies.</li><li>
Automation &amp; Observability: Proficiency in Python and Bash scripting, configuration management, and Infrastructure-as-Code tools (e.g., Ansible, Terraform). Experience with observability stacks (Grafana, Loki, Prometheus) for monitoring, logging, and building fault-tolerant systems.</li><li>
Solution Architecture &amp; Customer Engagement: Strong background in crafting scalable solutions and providing consultative support to customers, including leading architectural reviews and speaking publicly to executive partners.</li></ul>
Ways to Stand Out from the Crowd:<ul><li>
Knowledge of CI/CD pipelines for software deployment and automation.</li><li>
Experience working with NVIDIA GPU and Network Operators to manage automated resource lifecycle in Kubernetes environments.
</li><li>Solid hands-on knowledge of Kubernetes and container-based microservices architectures.</li><li>
Experience with NVIDIA GPU and Network Operator for automated GPU as well as network resources lifecycle management in Kubernetes environments.</li><li>
Experience with NVIDIA Base Command Manager (BCM) for provisioning, managing, and supervising GPU clusters at scale as well as background with RDMA-based fabrics (InfiniBand or RoCE) in HPC or AI environments.</li></ul></div>

Senior Solutions Architect, Cloud Infrastructure and DevOps

Concentrix

<div>Job Title:
Cloud &amp; AI Infrastructure / Endpoint Cloud Solution Architect (CSA) (Arabic-English)
Job Description
Technical Products and Services (TPS):
 
 
We're Concentrix. The intelligent transformation partner. Solution-focused. Tech-powered. Intelligence-fueled.
 
 
The global technology and services leader that powers the world&rsquo;s best brands, today and into the future. We&rsquo;re solution-focused, tech-powered, intelligence-fueled. With unique data and insights, deep industry expertise, and advanced technology solutions, we&rsquo;re the intelligent transformation partner that powers a world that works, helping companies become refreshingly simple to work, interact, and transact with. We shape new game-changing careers in over 70 countries, attracting the best talent.
 
 
The Concentrix Technical Products and Services team is the driving force behind Concentrix&rsquo;s transformation, data, and technology services. We integrate world-class digital engineering, creativity, and a deep understanding of human behavior to find and unlock value through tech-powered and intelligence-fueled experiences. We combine human-centered design, powerful data, and strong tech to accelerate transformation at scale. You will be surrounded by the best in the world providing market leading technology and insights to modernize and simplify the customer experience. Within our professional services team, you will deliver strategic consulting, design, advisory services, market research, and contact center analytics that deliver insights to improve outcomes and value for our clients. Hence achieving our vision.
 
 
Our game-changers around the world have devoted their careers to ensuring every relationship is exceptional. And we&rsquo;re proud to be recognized with awards such as &quot;World's Best Workplaces,&quot; &ldquo;Best Companies for Career Growth,&rdquo; and &ldquo;Best Company Culture,&rdquo; year after year.
 
 
Join us and be part of this journey towards greater opportunities and brighter futures.
JOB SUMMARY
The Cloud &amp; AI Infrastructure / Endpoint Cloud Solution Architect (CSA) is a senior technical role responsible for delivering end to end Azure infrastructure, identity, monitoring, resiliency, and cloud endpoint solutions. This role spans identity (Microsoft Entra ID), resiliency and protection (Azure Backup), hybrid infrastructure (Azure Local / Azure Stack HCI), observability (Azure Monitor), and cloud desktops (Azure Virtual Desktop and Windows 365). 
 
The CSA operates within Microsoft Global Delivery / CSU, delivering proactive, outcome-based engagements and supporting customer success through architectural guidance, design validation, deployment readiness, and operational excellence.
 
This role is designed to reflect multi skill CSA profiles supported by ESXP / OneProfile and Unified Skills Experience, where a CSA can hold multiple Azure and Endpoint skills in a single profile.
Responsibilities
<div>Azure Identity &amp; Access
 
<ul><li>Design and validate Microsoft Entra ID architectures including identity lifecycle, access governance, hybrid identity, and secure access patterns.
</li><li>Guide customers on identity integration with Azure Virtual Desktop, Windows 365, and Azure workloads.
</li><li>Ensure identity designs align with Zero Trust and Microsoft best practices. 
</li></ul></div><div> 
Azure Infrastructure Resiliency &amp; Protection
 
<ul><li>Architect and deliver Azure Backup solutions for IaaS, hybrid, and Azure Local environments.
</li><li>Design backup, restore, and disaster recovery strategies aligned with customer RPO/RTO requirements.
</li><li>Provide resiliency guidance for mission critical workloads. 
</li></ul></div><div> 
Hybrid Infrastructure (Azure Local / Azure Stack HCI)
 
<ul><li>Design, validate, and support Azure Local (Azure Stack HCI) deployments and integrations with Azure services.
</li><li>Guide customers on hybrid management, lifecycle operations, and modernization paths.
</li><li>Align hybrid infrastructure designs with Azure governance and monitoring standards. 
</li></ul></div><div> 
Observability &amp; Operations
 
<ul><li>Design and implement Azure Monitor solutions including Log Analytics, alerts, diagnostics, and operational insights.
</li><li>Enable customers to achieve operational visibility, performance monitoring, and proactive issue detection.
</li><li>Align monitoring strategies across Azure, hybrid, and endpoint workloads. 
</li></ul></div><div> 
Cloud Desktops &amp; Endpoint Virtualization
 
<ul><li>Architect and deliver Azure Virtual Desktop (AVD) and Windows 365 (W365) solutions.
</li><li>Guide customers on image management, identity integration, security, networking, and user experience optimization.
</li><li>Support enterprise adoption of cloud desktops as part of modern workplace and endpoint strategies. 
</li></ul></div><div> 
Delivery &amp; Engagement
 
<ul><li>Deliver Value Based Deliverables (VBDs), technical workshops, design reviews, and deployment assistance.
</li><li>Act as a trusted advisor, translating business requirements into secure, scalable architectures.
</li><li>Ensure accurate labor logging, profile completeness, and skills reviews in ESXP / OneProfile.
</li></ul></div>Qualifications
<div>Required Technical Skills
 
The CSA is expected to hold and maintain multiple skills concurrently, as supported by the Unified Skills Experience:
 
<ul><li>Microsoft Entra ID (Identity &amp; Access Management)
</li><li>Azure Backup
</li><li>Azure Local / Azure Stack HCI
</li><li>Azure Monitor
</li><li>Azure Virtual Desktop (AVD)
</li><li>Windows 365 (W365) 
</li></ul></div> 
Multiple skills in a single CSA profile are explicitly supported and encouraged within CSA Global Delivery and ESXP skill taxonomy. 
<div> 
Accreditations &amp; Readiness
 
<ul><li>Required or in progress CSA accreditations aligned to the above skills
</li><li>Ability to maintain skills and accreditations in accordance with dispatch and staffing standards
</li><li>Regular review and submission of skills every 90 days as per CSA tooling guidance 
</li></ul></div><div> 
Professional Capabilities
 
<ul><li>Strong architectural thinking across identity, infrastructure, operations, and endpoint services
</li><li>Excellent stakeholder communication and customer facing delivery skills
</li><li>Ability to operate across multiple solution areas while maintaining depth in primary skills
</li><li>Comfortable working in enterprise, regulated, and hybrid environments
 </li></ul></div>#LI-Remote #Egypt
Location:
EGY Work-at-Home
Language Requirements:
Time Type:
Full time</div>

Cloud & AI Infrastructure / Endpoint Cloud Solution Architect (CSA) (Arabic-English)

WinWire

<div>Location : Hyderabad/Bangalore
Job Description :
<ul>20+ years of comprehensive IT experience, including 8+ years in a Solution Architect or Enterprise Architect role in either Data Engineering &amp; Analytics or Application Development &amp; Infrastructure as the primary domain.
4+ years of cross-domain experience in the complementary domain (Data or App Dev/Infra), demonstrating architectural breadth.
Hands-on, deep expertise in Microsoft Azure, architecture, design, and implementation across compute, storage, networking, data, and security services; not limited to oversight.
Working proficiency in AWS and/or GCP, capable of designing, reviewing, and governing multi-cloud workloads across cloud platforms.
Practical application of Well-Architected Frameworks (Azure, AWS, or GCP) in production solution design, demonstrated hands-on implementation, not theoretical familiarity.
Demonstrated knowledge of TOGAF principles and their practical application in enterprise architecture governance and design.
Strong understanding of SRE principles, SLOs, error budgets, reliability patterns, and observability frameworks, with experience embedding these into engineering programs.
Demonstrated ability to leverage AI tools (GitHub Copilot, AI-assisted code review, automated testing, intelligent monitoring and incident analysis) to automate and standardize engineering practices, achieving simultaneous, measurable gains in team productivity and solution quality.
Proven ability to whiteboard solutions, drive structured solutioning workshops, and translate ambiguity into actionable architectural decisions.
Strong trade-off analysis and technology selection skills, able to evaluate options rigorously and recommend with clear rationale.
Experience defining solution and capability roadmaps aligned to business strategy and multi-year technology evolution.
Exceptional presentation and storytelling skills, able to communicate architecture clearly and persuasively to both technical teams and executive/business stakeholders.
Strong consulting and client-facing skills demonstrated ability to work with customers, technology partners, and internal SMEs across diverse stacks and domains, and influenced architectural decisions.
Robust integration skills across custom applications, data platforms, and COTS solutions.
Hands-on experience with CI/CD, DevOps toolchains, infrastructure-as-code, and automation practices.
Ability to balance technical contribution with team leadership, a practicing architect, not just a reviewer.
We are seeking a senior Enterprise Solution Architect who combines deep technical hands-on ability with the strategic foresight to shape architecture at enterprise scale. The ideal candidate brings a primary domain depth, either in Data Engineering &amp; Analytics or Application Development &amp; Infrastructure, backed by 8+ years in an Architect role, and meaningful cross-domain exposure in the secondary area (4+ years).A key differentiator for this role is the ability to strategically leverage AI tools to automate and standardize engineering practices, driving simultaneous improvements in team productivity and solution quality at scale.
</ul>
Key Skills: SRE practices, cloud architecture (Azure &amp; AWS / GCP), (Java/Python Programming/Dot Net) &amp; (Data Analytics/Data Engineering &amp; Infrastructure)</div>

Enterprise Architect - App Dev & Infra

The Ghani IT Solutions

Role Overview:We are seeking a Senior AI Engineer to architect and build a high-performance, custom Voice AI infrastructure. This role focuses on developing an end-to-end real-time audio processing pipeline and an intelligent NLP engine capable of synthesizing complex regulatory data into actionable insights with sub-second latency.Key Responsibilities:- Custom Voice Infrastructure: Develop a proprietary, low-latency audio pipeline integrating Speech-to-Text (STT), Large Language Models (LLMs), and Text-to-Speech (TTS).- Intelligent Data Parsing: Architect agentic workflows to ingest complex documentation and translate technical/legal jargon into plain-language summaries.- Real-time Audio Streaming: Manage full-duplex audio transmission using WebSockets and WebRTC to achieve human-like conversational responsiveness.- Automated Information Retrieval: Build scalable scrapers and API consumers to monitor high-frequency data sources and public registries for real-time updates.- Advanced RAG Systems: Implement sophisticated Retrieval-Augmented Generation (RAG) using Vector Databases to provide the AI with deep contextual awareness.Technical Requirements:- Programming: Expert-level Python; experience with asynchronous programming and high-concurrency systems.- NLP &amp; AI: Proven experience with LangChain, LlamaIndex, and fine-tuning open-source LLMs.- Speech Processing: Experience with real-time transcription (STT) and neural speech synthesis (TTS) engines.- Data Systems: Proficiency with Vector DBs (e.g., Pinecone, Milvus) and SQL/NoSQL databases.- Protocols: Strong understanding of WebSockets, WebRTC, and real-time data streaming.Location: DHA Phase 6, KarachiShift: MorningWork Location: In person

Senior AI & Machine Learning Engineer (Speech & NLP Specialist)

Integrant

<div>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 &amp; Business Development<ul><li>Partner with sales and solution teams to identify and qualify new opportunities</li><li>Lead or support technical presales activities: discovery workshops, RFP responses, architecture presentations</li><li>Build and deliver proof-of-concepts (POCs) that demonstrate platform capabilities to prospective clients</li><li>Prepare high-quality technical materials</li><li>Act as a trusted technical advisor during client conversations, proposing solutions aligned to business goals</li></ul> 
In-Account Delivery &mdash; SysOps &amp; DevOps Execution<ul><li>Operate directly within client accounts as a senior SysOps/DevOps engineer
</li><li>Run, troubleshoot, and optimize production-grade Kubernetes clusters and GPU/HPC environments hands-on</li><li>Own Linux system administration at a deep level: kernel tuning, storage, networking, performance profiling</li><li>Implement and maintain IaC pipelines, GitOps workflows, and CI/CD systems</li><li>Serve as the senior escalation point for complex operational incidents within accounts</li></ul> 
Architecture &amp; Solution Design<ul><li>Design end-to-end platform architectures spanning cloud, hybrid, and on-premises HPC environments</li><li>Define workload isolation models, networking architectures, and storage strategies for multi-tenant platforms</li><li>Recommend and validate technology choices aligned to client scale, budget, and team maturity</li><li>Produce architecture decision records (ADRs), solution blueprints, and technical runbooks</li></ul>
Technical Competencies &amp; Requirements
1. Architecture &amp; System Design<ul><li>Design production-grade multi-cluster Kubernetes platforms:</li><li>RKE2, EKS (AWS), AKS (Azure) at enterprise scale</li><li>GPU-aware clusters: NVIDIA H100 / A100 / B200 node pools</li><li>Hybrid cloud + on-premises HPC infrastructure</li><li>Define and document:</li><li>Workload isolation: namespaces, MIG partitioning, multi-tenancy models</li><li>Networking: BGP peering, Ingress controllers, service mesh (Istio / Cilium)</li><li>Storage: Longhorn, Ceph, distributed and high-throughput file systems</li></ul> 
2. Platform Engineering &amp; GitOps Strategy<ul><li>Define and enforce platform standards across the delivery lifecycle</li><li>GitOps tooling: ArgoCD, Fleet &mdash; declarative cluster management</li><li>CI/CD pipelines: Azure DevOps, Jenkins &mdash; build, test, promote</li><li>Infrastructure as Code: Terraform (modules, remote state, workspaces), Ansible</li><li>Standardize cluster bootstrapping, app deployment lifecycle, environment promotion (Dev QA Prod)</li></ul> 
3. AI / GPU Infrastructure Architecture (Priority Competency)<ul><li>Design and operate GPU compute platforms at scale:</li><li>GPU Operator deployment and lifecycle management</li><li>MIG (Multi-Instance GPU) partitioning for multi-tenant workloads</li><li>Advanced scheduling: Run:AI, Kubernetes-native GPU scheduling (device plugins)</li><li>Understand AI workload classes and their infrastructure implications:</li><li>Distributed training workloads (data/model/pipeline parallelism)</li><li>Inference pipelines &mdash; NVIDIA Triton Inference Server, TensorRT optimization</li><li>Align infrastructure to the full AI stack:</li><li>CUDA stack, cuDNN, NCCL collective communication libraries</li><li>High-speed networking: InfiniBand (HDR/NDR), RoCE for RDMA</li><li>GPUDirect RDMA / GPUDirect Storage for low-latency data paths</li></ul> 
4. Observability &amp; Reliability Engineering<ul><li>Define and implement full-stack observability:</li><li>Metrics: Prometheus, Thanos (long-term retention, multi-cluster)</li><li>Logs: Loki, Fluent Bit</li><li>GPU telemetry: DCGM Exporter, NVIDIA Nsight Systems</li><li>Build operational frameworks:</li><li>SLO / SLA definitions and error budget tracking</li><li>Alerting strategy &mdash; noise reduction, severity routing</li><li>Incident response playbooks and on-call runbooks</li></ul> 
5. Security &amp; Multi-Tenancy Architecture<ul><li>Design zero-trust security postures for multi-tenant platforms</li><li>Secret management: HashiCorp Vault, External Secrets Operator</li><li>Identity and access: IAM, RBAC, SSO/OIDC integration</li><li>Network isolation: NetworkPolicy, micro-segmentation, mTLS</li><li>Secure GPU sharing: MIG isolation, VGPU licensing, tenant boundary enforcement</li></ul> 
6. HPC, Data &amp; Storage Architecture (Priority Competency)<ul><li>Understand the high-performance storage for AI/HPC workloads:</li><li>GPUDirect Storage &mdash; bypassing CPU for GPU-native I/O</li><li>Distributed file systems: Weka (high-throughput NFS/S3), Ceph (scalable object/block)</li><li>Storage tiering, caching strategies, and data lifecycle management</li><li>Size and validate storage architectures against workload I/O profiles</li></ul> 
7. Operational Leadership &amp; Linux Systems<ul><li>Lead incident response and root cause analysis (RCA) for critical production issues</li><li>Define upgrade strategies, change management procedures, and disaster recovery plans</li><li>Write and maintain runbooks, operational playbooks, and knowledge base content</li><li>Integrate organizational processes, compliance requirements, and security policies into operational frameworks</li><li>Deep Linux expertise:</li><li>Kernel tuning (CPU governor, NUMA, IRQ affinity, hugepages)</li><li>Storage I/O scheduling, NVMe optimization</li><li>Network stack tuning for RDMA / InfiniBand</li><li>System performance profiling and bottleneck analysis</li></ul> 
Candidate Profile &mdash; Who You Are<ul><li>you are comfortable running production systems.</li><li>You have stronger SysOps and HPC depth than DevOps breadth, and you embrace that identity</li><li>You can shift fluidly between running a live incident, presenting an architecture to a CTO, and reviewing a POC demo environment</li><li>You communicate technical complexity clearly &mdash; to engineers and to C-level stakeholders</li><li>You understand why specific tooling choices matter (not just how to configure them) and can articulate trade-offs in presales conversations</li><li>You are comfortable owning outcomes across both commercial (presales) and delivery (operations) dimensions</li><li>You thrive in ambiguity and can scope both short POCs and long-horizon platform programs</li></ul> 
Requirements 
Required<ul><li>10+ years in platform/infrastructure engineering, with at least 2 years in architect-level role</li><li>Proven hands-on experience operating Kubernetes at scale in production (multi-cluster, multi-tenant)</li><li>Significant Linux systems administration experience &mdash; kernel, networking, storage at a low level</li><li>HPC and/or GPU infrastructure experience &mdash; physical GPU servers, NCCL, InfiniBand, or high-speed fabrics</li><li>Demonstrable presales or client-facing experience
</li><li>IaC experience: Terraform and/or Ansible in production environments</li><li>Strong understanding of GitOps and CI/CD pipelines in enterprise settings</li></ul> 
Strongly Preferred<ul><li>Experience with NVIDIA GPU Operator, MIG partitioning, Run:AI, or equivalent GPU scheduling tooling</li><li>Knowledge of distributed AI training infrastructure (PyTorch DDP, Horovod, DeepSpeed) from an infrastructure perspective</li><li>Familiarity with NVIDIA Triton Inference Server or TensorRT deployment pipelines</li><li>Experience with Weka, Ceph, or GPUDirect Storage in HPC/AI environments</li><li>Hands-on experience with Vault, External Secrets, and zero-trust network architectures</li><li>Exposure to bare-metal provisioning and HPC cluster management (Slurm, PBS, or equivalent)</li></ul> 
Certifications (Advantageous)<ul><li>CKA / CKS (Certified Kubernetes Administrator / Security Specialist)</li><li>RHCE / RHCA (Red Hat Certified Engineer / Architect)</li><li>AWS Solutions Architect / Azure Solutions Architect Expert</li><li>HashiCorp Terraform Associate or Vault Associate</li><li>NVIDIA DLI certifications (GPU computing, AI infrastructure)</li></ul></div>

Senior Lead SysOps/Devops Engineer

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