Job Purpose
Lead the overall Solutions and Presales function across Cloud, AI and Managed Services, providing strategic and technical leadership for enterprise and government customer engagements.
The role will own the end-to-end solutioning lifecycle from customer requirement discovery and solution strategy through architecture, proposal, commercials, technical validation and transition to delivery. The position will establish a unified solutioning framework across Cloud Infrastructure, AI/GPU Platforms and Managed Services, ensuring solutions are scalable, secure, commercially viable and aligned with the business strategy
Roles & Responsibilities
1. Solutions Strategy & Leadership
- Own and lead the overall solutioning strategy across Cloud, AI/GPU and Managed Services.
- Establish common solution architecture, design and governance standards across the three solution domains.
- Develop differentiated and repeatable solution frameworks, reference architectures, service models and solution blueprints.
- Align solution capabilities with business strategy, market opportunities, customer requirements and revenue objectives.
- Drive continuous innovation across cloud-native, AI, automation, observability, security and managed services.
2. Enterprise Solution Architecture
- Provide executive-level architectural leadership for complex, large-scale enterprise and government opportunities.
- Lead development of end-to-end solutions spanning compute, storage, networking, cloud, AI/GPU infrastructure, security, backup/DR, observability and managed services.
- Ensure integration of public, private, hybrid and sovereign cloud environments.
- Define architecture principles covering scalability, performance, security, compliance, availability and cost optimization.
- Review and approve solution architectures, BoQs, technical designs and major proposals.
3. AI & GPU Solution Leadership
- Lead AI Cloud and AI Factory solutioning covering GPU infrastructure, HPC, high-performance networking and AI platforms.
- Provide oversight on GPU sizing, workload architecture, distributed training/inference, Kubernetes, Slurm, InfiniBand/RoCE and high-performance storage.
- Guide architecture for GenAI, RAG, agentic AI and enterprise AI workloads.
- Drive adoption of emerging NVIDIA and other accelerator technologies and establish reusable AI reference architectures.
- Ensure AI solutions address performance, utilization, scalability, data sovereignty and commercial viability.
The underlying AI Architect JD specifically covers NVIDIA GPU clusters, InfiniBand/RoCE, GPU/CPU/memory/NVMe sizing, Kubernetes/Kubeflow, Slurm, vLLM/Triton/TensorRT-LLM and RAG/agentic AI.
4. Managed Services Solution Leadership
- Own the solutioning strategy for managed infrastructure, cloud operations, security, network, backup/DR, SOC/NOC, observability, automation and ITSM services.
- Define service catalog, SLA/KPI frameworks, operating models and transition approaches.
- Ensure managed services solutions are aligned with customer business outcomes, operational feasibility and commercial objectives.
- Establish strong solution-to-delivery governance and ensure effective transition of won engagements.
The existing Managed Services JD emphasizes requirement discovery, service design, RFP/RFI responses, SLA/KPI mapping, pricing, customer value and pre-sales-to-delivery transition.
5. Customer & CXO Engagement
- Act as the senior technology and solutioning interface for strategic customers and CXO stakeholders.
- Lead discovery workshops, solution presentations, technical negotiations, PoCs and executive-level discussions.
- Translate complex technology capabilities into clear business value, ROI, risk and transformation outcomes.
- Build trusted-advisor relationships with enterprise and government customers.
6. Pre-Sales & Business Enablement
- Partner with Sales and Business Development teams to identify, qualify and shape strategic opportunities.
- Lead solution strategy for large RFP/RFI, tenders and strategic bids.
- Ensure high-quality technical proposals, BoQs, SOWs, solution narratives and presentations.
- Drive solution competitiveness through differentiated architecture, service models and commercial constructs.
- Support deal strategy, technical negotiations and closure of strategic opportunities.
7. Commercial & Business Case Ownership
- Provide leadership on solution costing, pricing assumptions, capacity models and business cases.
- Ensure solutions balance technical excellence with commercial viability and target margins.
- Review major BoQs, partner/OEM proposals and commercial assumptions.
- Identify opportunities for standardization, reuse and optimization to improve solution profitability.
8. Technology Partners & OEM Ecosystem
- Build and manage strategic relationships with cloud, AI, infrastructure, security and managed services technology partners.
- Work with OEMs to develop joint reference architectures, solution offerings and GTM propositions.
- Evaluate emerging technologies and determine their relevance to the solution portfolio.
- Drive partner enablement and technical competency development across the solutions team.
9. Solution Governance & Quality
- Establish architecture and solution review mechanisms for strategic and complex opportunities.
- Ensure adherence to security, compliance, data sovereignty and regulatory requirements.
- Drive standardization of solution documentation, architecture reviews, costing models and handover processes.
- Ensure alignment between proposed solutions, available platform capabilities and delivery readiness.
10. Team Leadership & Capability Building
- Lead and develop a multidisciplinary solutions organization covering Cloud, AI/GPU and Managed Services.
- Define competency frameworks, role structures, KPIs and career paths for solution architects and specialists.
- Build a culture of technical excellence, customer centricity, collaboration and ownership.
- Mentor senior architects and develop future solution leaders.
- Create cross-functional collaboration between Product, Engineering, Operations, Sales, Security and Delivery teams.
Educational Qualifications
BE/B-Tech or equivalent with Computer Science or Electronics & Communication
Relevant Experience
- Experience: 15-20 years of overall IT experience, with a minimum of 3 years in GPU cloud architecture and design roles.
- Cloud Infrastructure Expertise: Proven track record in the design, operations, and maintenance of public/private cloud platforms, including service migration from on-premises to cloud or between enterprise data centers.
- Result-Oriented with Security Focus: Strong background in IT networking and cloud security, with the ability to address complex business needs in global, enterprise-scale environments.
- Deep knowledge of Azure, AWS, and GCP services, including native security controls, security centers, DDoS protection, firewalls, express route/direct connect, storage solutions, CDN, and site recovery.
- Proficiency with containerization and orchestration technologies (Kubernetes, Docker).
- Familiarity with enterprise platforms and tools such as, AWS EC2, AWS GuardDuty, AWS KMS, CloudWatch, AWS Lambda, and other modern cloud-native services.
- Private Cloud Technologies: Experience in OpenStack, VMware, Nutanix, and Kubernetes-based private cloud platforms, along with SaaS integration.
- Multi-Cloud & Hybrid Cloud: Skilled in design, deployment, and maintenance of hybrid/multi-cloud architectures with seamless connectivity and governance.
- Cloud Migration & Consulting: Strong expertise in cloud migration strategy, execution, and advisory consulting for enterprise clients.
- Soft Skills: Excellent communication, stakeholder engagement, and presentation skills with the ability to translate technical solutions into business value.
- Compliance & Identity Management: Experience in cloud networking, IAM (Identity & Access Management), governance, and compliance frameworks (ISO, PCI-DSS, DPDP, etc.)
