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AI Fullstack Developer - ONSITE - Riyadh, Saudi Arabia

0 years

0 Lacs

india

Posted:3 days ago| Platform: Linkedin logo

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Skills Required

ai developer orchestration openai mistral logic model routing monitoring exporting consulting excel word pdf latency compliance architecture gcc stack development python node.js react next.js strategies communication github

Work Mode

On-site

Job Type

Full Time

Job Description

You must be located in Riyadh, Saudi Arabia or open to traveling there and staying for 6 months.

  • 5 days a week onsite
{ALL EXPENSES WILL BE COVERED}

Role

You will be responsible for designing and developing Aiser’s

end-to-end AI platform

, including backend orchestration, frontend interfaces, and consensus pipelines across multiple AI providers.About the opportunity: We are building a next-generation AI-powered platform. The platform integrates multiple AI providers to deliver specific outputs.

Responsibilities

  • Architect and implement multi-provider orchestration pipelines (OpenAI, Claude, DeepSeek, Mistral, Perplexity, etc.)
  • Develop consensus logic to merge, cross-verify, and rank model outputs.
  • Build scalable backend infrastructure (APIs, secure model routing, monitoring).
  • Deliver intuitive frontend interfaces for exporting consulting deliverables (PPT, Excel, Word, PDF, CSV).
  • Implement RAG pipelines (vector DBs, embeddings) for knowledge-based consulting.
  • Optimize for performance, latency, and cost (premium vs. bulk AI usage).
  • Ensure compliance-ready architecture suitable for global rollouts (US/EU/GCC).

Requirements

  • Proven experience in AI full-stack development (backend + frontend + AI model orchestration).
  • Hands-on with multiple LLM providers (at least 3 of: OpenAI, Anthropic, DeepSeek, Mistral, Perplexity).
  • Strong backend skills (Python, Node.js) and frontend frameworks (React/Next.js).
  • Expertise with vector databases (Pinecone, Weaviate, FAISS) and RAG systems.
  • Experience in exporting structured consulting deliverables (PPT, Excel, Word, PDF).
  • Strong understanding of AI cost/latency trade-offs and fallback strategies.
  • Excellent communication and ability to document architecture clearly.
  • Candidates must provide at least 2 case studies (e.g., demo links, GitHub repos, architecture slides, or project briefs) demonstrating: Multi-provider AI orchestration or consensus systems. Full-stack AI platform development with consulting/business deliverables.

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