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Urgent! Engineering Director Job Opening In Abu Dhabi – Now Hiring beBeeLeader

Engineering Director



Job description

Key to our organization's success is the role of a seasoned Engineering Leader, responsible for driving large-scale AI systems towards world-class standards in scalability, safety, and performance.

This leader bridges cutting-edge research with enterprise-grade infrastructure, steering excellence across product development, cloud and on-premises operations, and AI model integration.

Through innovation and strategic vision, they reinforce our position as a global pioneer in sovereign, responsible, and resilient AI infrastructure for international partnerships.

Key Responsibilities

  • Lead the end-to-end development and operation of AI product platforms, ensuring timely delivery and high-quality results.

  • Design and maintain scalable, secure, and high-availability architectures across hybrid cloud and on-premise environments, balancing technical expertise with business acumen.

  • Implement modern DevOps pipelines (Kubernetes, Docker, CI/CD, GitHub Actions) for reliable model deployment and service uptime, fostering collaboration among cross-functional teams.

  • Oversee API design, data flow, and backend system integration to support model training, inference, and analytics, guaranteeing seamless data exchange and efficient workflows.

Qualifications & Technical Experience Required

  • Bachelor's or Master's in Computer Science, Engineering, or a related discipline (PhD preferred)
  • 8-10 years in software engineering, infrastructure management, or AI systems and at least 3 years in a leadership capacity, showcasing a strong track record of delivering complex projects on time and within budget.

  • Proven experience in: Kubernetes, Docker, CI/CD and systems observability tools, demonstrating hands-on familiarity with open-source technologies.

  • AWS Cloud Management: EKS, EC2, S3, RDS, IAM, CloudWatch, Route 53, with a deep understanding of cloud security and compliance best practices.

  • On-prem & Co-location Data Center Operations: GPU cluster orchestration, network configuration, and storage optimization, highlighting expertise in managing hybrid infrastructure.

  • AI Ecosystem & LLMs: hands-on familiarity with open-source and commercial models (Llama, Qwen, Jais, Mistral, OpenAI, Anthropic, etc.), leveraging knowledge of emerging trends and innovative solutions.

  • MLOps & Model Serving: vLLM, Triton, MLflow, Ray, or Hugging Face Transformers, with a focus on deploying models efficiently and effectively.

  • AI Security & Red Teaming: prompt defense, guardrail systems, toxicity and bias detection, model evaluation frameworks, demonstrating a commitment to responsible AI practices.

  • Strong foundation in Python, Bash, and system-level automation, with excellent problem-solving skills and attention to detail.

  • Demonstrated success in managing complex technical programs and delivering strategic outcomes, with a proven ability to adapt to changing priorities and meet deadlines.

  • Excellent communication, stakeholder management, and leadership skills, with a collaborative approach to team building and professional growth.


Required Skill Profession

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