Senior technical architect position cloud computing . Jobs

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Infrastructure Architect

Accenture -
Gurugram, Haryana

Apply Now

Job details

Full-time

Qualifications

TensorFlow
Cloud infrastructure
Azure
Kubernetes
Ansible
AWS
Docker
Virtualization
Terraform
VMWare
Weka
AI
Communication skills

Full job description

Project Role : Infrastructure Architect
Project Role Description : Lead the definition, design and documentation of technical environments. Deploy solution architectures, conduct analysis of alternative architectures, create architectural standards, define processes to ensure conformance with standards, institute solution-testing criteria, define a solutions cost of ownership, and promote a clear and consistent business vision through technical architectures.
Must have skills : Infrastructure Automation
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary:
As an Infrastructure Architect, a typical day involves leading the design and documentation of complex technical environments that support organizational goals. This role requires deploying solution architectures and evaluating various architectural alternatives to determine the most effective approach. The professional ensures that architectural standards are clearly defined and adhered to, while establishing processes that maintain consistency and quality across projects. Additionally, the role includes setting criteria for solution testing and assessing the total cost of ownership for proposed solutions. Throughout the day, the Infrastructure Architect works to align technical strategies with the broader business vision, fostering clarity and coherence in architectural decisions.

Key Responsibilities:
Design and implement HPC and AI infrastructure solutions, aligning system architecture and deployment roadmaps to industry-specific performance and scalability needs
Deploy, configure, and manage XPU-based clusters (CPU/GPU/accelerators) using schedulers, VM/K8s orchestration platforms, Slurm, and containerized platforms in scalable designs to provide Metal as a Service (MaaS), GPUaaS, AIaaS, and other offerings
Optimize cluster performance, scalability, energy, and cost efficiency across on-premises, cloud, and hybrid environments
Integrate AI and HPC platforms with existing IT systems, data pipelines, and security frameworks
Monitor, troubleshoot, and tune infrastructure to ensure high availability, low-latency networking, and workload resiliency
Develop and maintain documentation including architecture diagrams, configuration baselines, and operational runbooks
Provide Provide technical guidance and support to users, enabling efficient execution of HPC/AI workloads, large-scale models, and simulations.

Required Skills and Qualifications:

Proven ability to advise and engage with C-Suite executives and senior leadership, translating complex AI and HPC technologies into business and strategic value
Deep knowledge of infrastructure components including XPUs, high-performance fabrics (InfiniBand, Ethernet), and modern storage/data platforms (e.g. NVMe-oF, Lustre, BeeGFS, VAST, DDN, Weka)
Familiarity with orchestration and management frameworks (Slurm, Kubernetes, Docker) and performance/monitoring tools for AI/HPC environments
Strong grasp of MLOps, DevSecOps, and automation principles (Terraform, Ansible) as they apply to large-scale, secure, and reproducible workflows Experience in AgenticAI based automation developing and integrating agents for automation and observability
Excellent communication and client-facing skills, with the ability to present complex architectures to both executives and technical teams.

Preferred Skills and Qualifications:

Understanding of cloud and virtualization platforms (AWS, Azure, GCP, VMware, Nutanix) and how to align them with AI/HPC workload requirements
Experience advising or overseeing large-scale AI/HPC deployments (1,000+ GPUs or clusters of 100+ servers), providing architecture and strategic guidance
Familiarity with GPU computing and accelerator ecosystems (NVIDIA CUDA, AMD ROCm) and integration considerations for HPC/AI workloads
Knowledge of AI/ML frameworks (TensorFlow, PyTorch) and their operational and performance implications in HPC/AI environments
Industry experience in Life Sciences, Resources, Automotive, Financial Services, Telecommunications, or other HPC/AI-intensive sectors
Relevant cloud or infrastructure certifications (e.g., AWS Solutions Architect, GCP Professional Data Engineer) or equivalent technical credentials
Experience in workload planning, optimization, and orchestration guidance to align infrastructure with business and research objectives
Demonstrated ability to develop roadmaps, ROI analysis, and architecture recommendations that balance performance, scalability, and cost efficiency

Additional Information:

The candidate should have minimum 12 years of experience in Infrastructure Automation.
This position is based at our Gurugram office.
A 15 years full time education is required.

15 years full time education

Apply Now

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