Bengaluru Karnataka Director sre cloud operations Jobs – 25 Open Jobs Today

Director | Hybrid cloud | Bengaluru | Engineering | Hybrid Cloud Engineering
Deloitte —Bengaluru, Karnataka
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Honeywell —Bengaluru, Karnataka
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Director – IT Infrastructure Services (Managed Services)
INOPTRA DIGITAL —Bengaluru, Karnataka
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Director, Technical Program Management - Integrated Service Delivery
EPAM Systems, Inc. —Bengaluru, Karnataka
- Azure
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- Paid time off
Cloud Infrastructure & Site Reliability Engineer (DevOps + SRE + CloudOps)
Mishipay —Bengaluru, Karnataka
- Azure
- DevOps
- Databases
- Food provided
Quick apply
Manager, Network Operations Center
Applied Systems India Private Limited —Bengaluru, Karnataka
- Full-time
- Azure
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Senior Director-Technology
Genpact —Bengaluru, Karnataka
- Full-time
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- DevOps
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Director, Platform Engineering
Amadeus IT Group —Bengaluru, Karnataka
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Senior Director of Observability Engineering , ITC
Nike —Bengaluru Urban District, Karnataka
- Full-time
- Computer Science
- Research
- Bachelor's degree
Senior Director - Forward Deployment
Microland —Bengaluru, Karnataka
- Master's degree
- Bachelor's degree
Director of Quality Engineering & Automation
Harness.io —Bengaluru, Karnataka
- Computer Science
- Bachelor's degree
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Associate Director - Forward Deployment
Microland —Bengaluru, Karnataka
- Master's degree
- Bachelor's degree
Director Software Engineering
Hewlett Packard Enterprise —Bengaluru, Karnataka
- Full-time
- Computer Science
- DevOps
- SQL
Director of Quality Engineering & Automation
Harness —Bengaluru, Karnataka
- Computer Science
- Bachelor's degree
- APIs
Quick apply
Staff Site Reliability Engineer (Linux/Network troubleshooting/Scripting)
Zscaler —Bengaluru, Karnataka
- DevOps
- SQL
- AWS
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6h
Engineering Manager (Python/Django)
Mishipay —Bengaluru, Karnataka
- Remote
- Azure
- Management
- Machine learning
- Food provided
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Senior Manager, Software Engineering
DocuSign —Bengaluru, Karnataka
- Hybrid work
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- Computer Science
- B.Sc
Manager, Software Engineering, ITC
Nike —Bengaluru Urban District, Karnataka
- Full-time
- DevOps
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ML Ops and Data Engineer
PinnacleU —HSR Layout, Bengaluru, Karnataka
- ₹34,50,000 - ₹35,00,000 a year
- Full-time
- DevOps
- Master's degree
- APIs
Quick apply
12d

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Director | Hybrid cloud | Bengaluru | Engineering | Hybrid Cloud Engineering

Deloitte -
Bengaluru, Karnataka

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Job details

12 days ago

Qualifications

Kubernetes
Software deployment
Firmware
Business development
Embedded software
Linux
AI
Leadership

Full job description

Director | Hybrid cloud | Bengaluru | Engineering | Hybrid Cloud Engineering

Job requisition ID : 111027
Location: Bengaluru
Entity: Deloitte Touche Tohmatsu India LLP

The team

The team must do much more than keep the wheels turning; it is the engine that drives functional excellence and the enabler of innovation and long-term growth.

Key responsibilities

Own end-to-end architecture across NVIDIA GPU compute, CPU/DPU, management nodes, control plane, high-speed fabrics, storage, backup and security.
Design and deploy DGX/HGX or NVIDIA-certified GPU clusters and select fit-for-purpose GPU platforms for training, fine-tuning, visualization, batch inference and real-time inference.
Architect InfiniBand, Spectrum-X Ethernet and RoCE networks, including topology, rail optimization, congestion control, OOB management, telemetry and performance engineering.
Define high-performance file and object storage architectures covering checkpointing, data staging, metadata, throughput, IOPS, resiliency and data lifecycle requirements.
Engineer AI data-centre requirements covering rack layout, GPU density, power, cooling, cabling, physical resilience, capacity expansion and DCIM/monitoring integration.
Implement Kubernetes/OpenShift and/or Slurm-based platforms, including GPU scheduling, NVIDIA GPU/Network Operators, MIG, quotas, tenancy, workload isolation and policy enforcement.
Integrate and operationalize NVIDIA AI Enterprise, CUDA, NCCL, NIM, NeMo, Triton, DCGM and approved AI model/runtime services.
Establish automated provisioning, firmware and driver lifecycle management, image management, validation, burn-in, acceptance testing and performance benchmarking.
Operate the platform using SRE principles, with comprehensive observability, incident and problem management, capacity planning, patching, disaster recovery and security controls.
Optimize GPU utilization, job throughput, tokens per second, workload performance, energy efficiency and cost per workload.
Own the market proposition, account strategy, pipeline development, strategic alliances and executive relationships for AI infrastructure services.
Shape multi-year AI infrastructure transformation programmes and lead commercial negotiations, governance, delivery quality, risk management and business economics.
Build, mentor and retain a nationally recognized team of AI data-centre, GPU, network, storage, cloud and platform engineering specialists.

Required skills

Typically 18+ years of experience across infrastructure, cloud, data-centre, HPC or platform engineering, including substantial leadership of production AI/GPU environments.
Proven experience in business development, executive advisory, strategic alliances and governance of large-scale technology programmes.
Strong expertise in NVIDIA GPU architectures and systems, including DGX/HGX or equivalent certified platforms.
Proven experience designing GPU clusters across compute, high-speed networking, storage, control plane and management plane.
Strong understanding of AI workload characteristics, including distributed training, fine-tuning, RAG, batch inference, real-time inference and HPC.
Hands-on architecture and leadership experience with Kubernetes/OpenShift and/or Slurm, including GPU scheduling, partitioning, quotas, workload isolation and multi-tenancy.
Strong Linux, container, CUDA ecosystem, NCCL, GPU driver, firmware and GPU observability fundamentals.
Proven experience with production AI infrastructure covering security, resilience, capacity management, performance optimization, automation and day-2 operations.
Strong understanding of high-density data-centre environments, including power, cooling, physical networking, rack-scale deployment and facility dependencies.
Experience designing and operating high-performance storage and InfiniBand/Ethernet fabrics for distributed AI and HPC workloads.
Strong commercial, stakeholder-management and executive-communication capabilities.

Experience across AI factories, GPU clouds, HPC centres, enterprise AI data centres, GCCs, OEMs or colocation facilities.
Exposure to NVIDIA DGX/HGX, NVIDIA AI Enterprise, Spectrum-X, InfiniBand, BasePOD, SuperPOD or NVIDIA validated reference architectures.
Experience with NVIDIA-certified infrastructure and production-scale AI platform deployments.
Relevant certifications such as CKA/CKS, Red Hat, NVIDIA, Linux, networking, storage or data-centre certifications.
Experience building AI infrastructure practices, centres of excellence or nationally scaled specialist engineering teams.

Production-ready, secure, resilient and scalable NVIDIA GPU infrastructure.
High GPU utilization, predictable application performance and reduced time to onboard AI workloads.
Reliable capacity expansion with automated provisioning, validation and lifecycle management.
Measurable improvements in workload throughput, energy efficiency and cost per workload.
Strong platform reliability, observability, security and operational maturity.
High client satisfaction, consistent delivery quality and reusable engineering accelerators.
Strong market positioning, strategic partnerships and sustainable AI infrastructure pipeline.
A high-performing, nationally recognized AI infrastructure engineering organization.

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director sre cloud operations jobs in bengaluru karnataka

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