AI Solutions Architect – SupportFinity

Role Overview SupportFinity is hiring an AI Solutions Architect to lead the design and delivery of...

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عمل كلي

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Role Overview

SupportFinity is hiring an AI Solutions Architect to lead the design and delivery of AI-powered video, audio, and text solutions deployed on highly secure, closed hardware environments.

This role sits at the intersection of AI, software, and hardware. You will architect end-to-end AI systems—powered by LLMs running directly on dedicated hardware devices—with a strong focus on security, performance, and multilingual intelligence (Arabic & English).

You will own the technical vision, translate complex use cases into deployable AI architectures, and lead implementations for restricted, offline, or air-gapped environments where cloud dependency is not an option.

What You’ll Do

AI Architecture & Design

  • Design AI-powered video, audio, and text pipelines optimized for secure hardware devices
  • Architect on-device or edge-deployed LLM solutions with minimal or zero cloud reliance
  • Lead AI system design for closed, controlled, and highly regulated environments

Hardware–Software Integration

  • Design AI solutions that operate within hardware constraints (compute, memory, latency, power)
  • Work closely with hardware, firmware, and systems teams to ensure seamless integration
  • Optimize models and inference pipelines for specific chipsets, accelerators, and embedded platforms

Multilingual Intelligence

  • Architect and fine-tune AI systems capable of high-quality Arabic and English understanding
  • Design multilingual NLP, speech-to-text, text-to-speech, and video intelligence pipelines
  • Address linguistic nuance, dialect sensitivity, and cross-language reasoning

Security & Reliability

  • Design AI systems aligned with secure-by-design principles
  • Ensure data isolation, controlled model access, and compliance with strict security requirements
  • Build architectures suitable for air-gapped, offline, or sovereign environments

Technical Leadership

  • Own AI design decisions from use-case definition → architecture → deployment
  • Lead technical reviews, architecture documentation, and stakeholder alignment
  • Act as the AI authority for complex, high-impact customer and internal projects

Required Experience & Skills

Core Requirements

  • 5+ years of experience across AI, software architecture, and system design
  • Proven experience designing AI solutions for secure, closed, or embedded hardware environments
  • Strong hands-on experience with LLMs (inference, fine-tuning, optimization, deployment)
  • Deep understanding of hardware–software co-design
  • Ability to independently lead AI architecture from concept to production

AI & ML Expertise

  • Experience with NLP, speech, video, or multimodal AI systems
  • Model optimization techniques (quantization, pruning, distillation, edge inference)
  • Familiarity with deploying AI on constrained or specialized hardware

Languages

  • Strong experience building AI systems in Arabic and English
  • Ability to handle multilingual data pipelines and linguistic edge cases

Technical Stack (Representative)

  • LLM frameworks and runtimes
  • Python, C/C++, or equivalent system-level languages
  • Model deployment frameworks for edge / embedded AI
  • Secure system design and data isolation practices

Work location

  • You’ll work in a hybrid mode. Our office is in Smart Village, Giza where you will need to be present in office at least once a week.

Nice to Have

  • Experience with air-gapped or sovereign AI deployments
  • Background in defense, telecom, critical infrastructure, or regulated industries
  • Experience working with custom silicon, NPUs, GPUs, or AI accelerators
  • Familiarity with privacy-preserving AI techniques

Why Join SupportFinity

  • Design real-world AI systems that operate where cloud AI cannot
  • Work on cutting-edge AI deployed on secure hardware, not demos
  • Lead architecture for mission-critical, high-impact systems
  • Collaborate with a senior team building AI-native platforms from the ground up
  • Competitive compensation, meaningful ownership, and long-term growth

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