Senior Solutions Architect, Generative AI

NVIDIA
Mumbai
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringEducation: mastersSkills: ["Communication","Collaboration","Technical leadership","Workshop facilitation","Presenting complex concepts"]

Architect end-to-end generative AI solutions centered on LLMs and Retrieval-Augmented Generation (RAG). Partner with customers to define language-related challenges and design tailored workflows, while supporting pre-sales with demos and technical presentations. Lead workshops and guide training and optimization of LLMs using NVIDIA platforms and GPUs, including RAG integration into customer applications and production inference deployment.

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FursaFursa
NVIDIA
NVIDIA
2 hours ago

Senior Solutions Architect, Generative AI

âś“ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live
Reposted: similar role first listed 7 months ago

Job Summary

Architect end-to-end generative AI solutions centered on LLMs and Retrieval-Augmented Generation (RAG). Partner with customers to define language-related challenges and design tailored workflows, while supporting pre-sales with demos and technical presentations. Lead workshops and guide training and optimization of LLMs using NVIDIA platforms and GPUs, including RAG integration into customer applications and production inference deployment.
Location: Mumbai
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Architect end-to-end generative AI solutions focused on LLMs and RAG workflows.
  • •Collaborate with customers to understand language-related business challenges and design tailored solutions.
  • •Support pre-sales activities with sales and business development teams, including technical presentations and demonstrations.
  • •Lead workshops and design sessions to define and refine LLM- and RAG-based solutions, including training and optimization of LLMs on NVIDIA platforms.
  • •Design and implement RAG workflows and guide integration into customers’ applications and systems, while keeping up with developments in language models.

Key Requirements

  • •Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
  • •5+ years of hands-on experience in a technical role focused on generative AI and training LLMs.
  • •Proven track record deploying and optimizing LLM models for production inference.
  • •In-depth understanding of state-of-the-art language models (e.g., GPT-3, BERT).
  • •Expertise training and fine-tuning LLMs using TensorFlow, PyTorch, or Hugging Face Transformers.
Experience:Generative aiLlmsRagGpuProduction inference
Education:Master's
Skills:CommunicationCollaborationTechnical leadershipWorkshop facilitationPresenting complex concepts
Tech Stack:Large Language Models (LLMs)RAGTensorFlowPyTorchHugging Face TransformersGPT-3BERTAWSAzureGCPDockerKubernetesGPUsGPU cluster architectureParallel processingDistributed computing

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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