AI Solution Architect I

Job Summary

We are seeking an experienced AI Solution Architect to drive solution architecture, technical pre-sales, and AI transformation initiatives within HCLTech's NVIDIA Ecosystem. The role will partner with NVIDIA, sales, delivery, and customer stakeholders to design enterprise AI solutions leveraging AI Factory, accelerated computing, enterprise GenAI, and NVIDIA technologies. In addition to solution architecture, the role will lead pre-sales support, proposal and collateral development, Go-to-Market (GTM) initiatives, and NVIDIA alliance ecosystem engagement to accelerate customer adoption and business growth.

Key Responsibilities

• AI Solution Architecture: Design end-to-end AI solutions leveraging NVIDIA technologies including AI Factory, DGX, HGX, NVIDIA AI Enterprise, NIM, NeMo, Omniverse, CUDA, accelerated computing, and enterprise GenAI platforms.
• Technical Pre-sales & Sales Pursuit Support: Partner with sales and business development teams to lead customer discovery workshops, solution architecture discussions, technical presentations, demonstrations, and strategic AI pursuits.
• Proposal & Solution Collateral Development: Create high-quality technical proposals, reference architectures, solution blueprints, whitepapers, reusable collateral, and customer-facing assets aligned with NVIDIA AI solutions and HCLTech offerings.
• Go-to-Market (GTM) Development: Develop industry-specific AI offerings, use cases, value propositions, ROI frameworks, and GTM assets to accelerate customer adoption and drive business growth.
• NVIDIA Alliance Ecosystem Support: Collaborate with NVIDIA, alliance managers, practice teams, and delivery organizations to develop joint solutions, support partner initiatives, drive co-sell opportunities, and strengthen the NVIDIA ecosystem.
• Industry Solution Development: Build scalable AI solutions and reference architectures across Manufacturing, BFSI, Healthcare, Retail, Telecom, Public Sector, and other industry verticals.
• Knowledge Management & Reusable Assets: Establish and maintain a centralized repository of solution assets, customer success stories, competitive intelligence, best practices, and reusable technical content.
• Training & Capability Building: Conduct technical enablement sessions, workshops, certification programs, and mentoring to strengthen NVIDIA AI capabilities across sales, pre-sales, and delivery teams.
• Cross-functional Collaboration: Work closely with global sales, delivery, AI Labs, alliance teams, engineering, and product teams to ensure successful solution development and customer outcomes.

Skill Requirements

• 8–12 years of experience in Solution Architecture, AI/Cloud Consulting, Technical Pre-sales, or Enterprise Solutioning.
• Experience supporting large enterprise pursuits, RFPs/RFIs, solution proposals, and customer workshops.
• Experience working with global customers, alliance partners, and cross-functional teams.

• Technical Skills

  • Strong understanding of Generative AI, LLMs, AI Agents, RAG, AI platforms, machine learning, and enterprise AI architectures.
  • Knowledge of NVIDIA technologies such as AI Enterprise, DGX/HGX, CUDA, NIM, NeMo, Omniverse, AI Factory, GPU infrastructure, or accelerated computing.
  • Experience with Azure, AWS, or Google Cloud AI services and enterprise AI deployment architectures.
  • Familiarity with Kubernetes, containers, APIs, MLOps, and AI infrastructure is desirable.
  • Strong presentation, proposal writing, and architecture documentation skills.

Other Requirements

• trong customer consulting, stakeholder management, and executive communication skills.
• Ability to manage multiple strategic pursuits and priorities simultaneously.
• Excellent analytical, problem-solving, and collaboration skills.
• Self-driven with the ability to work effectively across global teams.

Education

• Bachelor's degree in Engineering, Computer Science, Information Technology, or a related discipline.
• Master's degree or MBA is an added advantage.
• NVIDIA AI, Cloud, or AI/ML certifications are preferred.