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Lead AI Engineer – Agentic Systems

Neural Horizons AI | Agentic AI, Growth Systems & Business Transformation
Dubai, UAE
Contract
Mid-Senior
Onsite
Discovered 2 weeks ago
Computer science fundamentalsSoftware developmentData structures and algorithmsSystem designProduction-grade codingNeural networks
Free

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Computer science fundamentalsSoftware developmentData structures and algorithms
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Company Description

Neural Horizons AI helps GCC businesses use artificial intelligence and digital marketing to improve growth and transformation.

The company works across machine learning, automation, predictive analytics, and digital marketing for SMEs and enterprises.

Its approach combines business assessment, tailored AI strategy, and deployment of intelligent solutions.

Role Description

This is a full-time, on-site Lead AI Engineer role based in Dubai.

The role designs, builds, and deploys agentic AI systems for business transformation, growth optimization, and AI-powered customer and marketing experiences.

The position includes scalable AI architecture, end-to-end model development, production NLP and neural network integration, technical roadmaps, code quality oversight, mentoring, and AI strategy.

Core Responsibilities

  • Architect scalable AI solutions and lead end-to-end model development.
  • Integrate neural networks and NLP components into production systems.
  • Translate business requirements into technical roadmaps with cross-functional stakeholders.
  • Oversee code quality and software development practices.
  • Guide experimentation and pattern recognition for complex data sets.
  • Ensure models meet robustness, security, performance, and compliance standards.
  • Mentor junior engineers and contribute to AI strategy.
  • Explore tools and frameworks to improve agentic AI capabilities.

Qualifications

  • Require strong computer science and software development foundations, including data structures, algorithms, system design, and production coding.
  • Require experience designing, training, and evaluating deep learning models for real-world applications.
  • Require hands-on NLP experience with transformer architectures and language model deployment.
  • Require experience leading AI engineering teams or projects and defining technical roadmaps.
  • Require fluency in common AI/ML technology stacks, MLOps frameworks, and cloud platforms.
  • Experience with agentic or autonomous AI systems, orchestration frameworks, or multi-agent architectures is highly beneficial.
  • Require a bachelor’s or master’s degree in a relevant field or equivalent practical experience.
  • Require strong problem-solving, communication, and cross-functional collaboration skills.

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