Hybrid Cloud Presales Consultant

Hybrid Cloud & Public Cloud Pre-Sales Consultant

Location: Noida, Bengaluru, Chennai, Pune

Experience: 3-12 Years

Role Summary

Support hybrid cloud pre-sales engagements by designing solutions across on-prem, private, and public cloud environments. Work closely with sales and delivery teams to build customer-centric solutions.

Key Responsibilities

• Support technical presales engagements for datacenter, hybrid cloud, private cloud, public cloud, automation, operations and AI infrastructure opportunities.
• Participate in discovery discussions and customer workshops to understand current-state infrastructure, pain points, transformation objectives, business priorities and budget considerations.
• Translate customer requirements into solution architectures covering compute, storage, backup, network, virtualization, security, automation, observability and cloud operations.
• Develop solution proposals, high-level architectures, BoMs, sizing assumptions, SoW inputs, migration approaches and implementation assumptions.
• Support RFP/RFI responses with clear technical, operational and commercial inputs.
• Prepare and deliver customer presentations, solution walkthroughs, whiteboarding sessions, demos and PoCs.
• Collaborate with OEMs and technology partners.
• Position infrastructure modernization solutions and cloud operating models.
• Contribute to automation and operations transformation solutions covering SRE, AIOps, observability, ITSM integration, infrastructure as code and runbook automation.
• Support AI Factory and AI-ready infrastructure solutioning across GPU compute, high-performance networking, storage, Kubernetes/container platforms, MLOps/LLMOps and operational governance.
• Explain Agentic AI use cases for IT and cloud operations, such as intelligent ticket triage, root cause analysis, autonomous remediation, autonomous Finops, knowledge assistants, change-risk insights and workflow agents.
• Maintain reusable presales assets including proposal templates, architecture patterns, demo narratives, reference BoMs and competitive positioning material.

Required Skills

• Presales and solutioning: Experience in IT infrastructure, datacenter, cloud, automation, operations or transformation presales; ability to convert requirements into solution outcomes.
• Datacenter foundation: Understanding of servers, storage, backup, network, virtualization, operating systems, databases, disaster recovery, security and enterprise availability requirements.
• Private cloud and SDDC: Exposure to VMware VCF/vSAN/Aria, Nutanix, Azure Stack HCI, OpenStack, Red Hat OpenShift virtualization or similar private cloud/SDDC platforms.
• Public cloud: Working understanding of AWS, Microsoft Azure and/or Google Cloud; ability to discuss landing zones, migration, connectivity, identity, backup, security, resiliency and cost/performance considerations.
• Hybrid cloud architecture: Ability to position hybrid operating models, workload placement, migration waves, cloud management, governance, cost optimization and operational runbooks.
• Automation: Exposure to Ansible, Terraform, PowerShell/Python scripting, CloudFormation/Bicep, GitOps, CI/CD or equivalent automation tooling.
• Operations transformation: Understanding of ITIL/ITSM, SRE, observability, monitoring, logging, tracing, event management, CMDB integration, AIOps and product-driven delivery models.
• Proposal development: Ability to create solution notes, architecture diagrams, BoM inputs, SoW assumptions, RFP/RFI responses, effort assumptions and risk/constraint statements.
• Customer communication: Strong listening, presentation, storytelling and documentation skills; ability to articulate customer pain points and map them to practical technology and commercial solutions.
• Understanding of AI Factory concepts: Full-stack AI Factory infrastructure designed to build, train, tune, deploy and operate AI workloads at enterprise scale.
• AI Factory Building Blocks: Exposure to AI-ready infrastructure building blocks.
• Awareness of MLOps/LLMOps concepts including data pipelines, model lifecycle, model registry, inference endpoints, prompt/model evaluation, monitoring and governance.
• Understanding of GPU virtualization, workload scheduling, data locality, storage throughput, network latency and resiliency considerations for AI workloads.
• Agentic AI: Ability to translate IT operations problems into AI assistant and agent workflows, such as incident triage, root cause analysis, remediation, capacity insights, compliance checks, FinOps and knowledge automation.
• Hands-on PoC or demo experience with GenAI or Agentic AI is preferred.

Nice to Have

• Experience in pre-sales or solution architecture
• Awareness of multi-hypervisor environments
• Basic understanding of security and cloud governance