Lead AI Engineer (AI)

Location: Cairo, Egypt; hybrid workplace

Company

hirify.global.

What you will do

• Lead end-to-end technical implementation of AI/ML projects from prototyping and experimentation through production deployment and optimization.
• Design and review architectures covering data pipelines, model serving, vector databases, RAG systems, and agentic workflows.
• Guide development of classical ML models for prediction, ranking, recommendation, scoring, and time-series forecasting, as well as GenAI solutions including RAG, AI agents, and LLM applications.
• Evaluate classical ML, LLMs, fine-tuning, and hybrid approaches based on accuracy, cost, performance, and maintainability.
• Provide hands-on technical guidance, conduct code and architecture reviews, and mentor AI engineers, including hiring and people management.
• Drive engineering practices for testing, CI/CD, MLOps, monitoring, security, data privacy, responsible AI, and reusable AI components while collaborating with product, data, engineering, and business stakeholders.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 6+ years of experience in AI, ML, or data science roles, including 1+ year leading a team of engineers.
• Proven experience building and deploying classical ML models, including gradient boosting, regression, classification, recommender systems, or time-series forecasting.
• Strong knowledge of feature engineering, model validation, and experiment design including A/B testing.
• Proven experience designing and deploying GenAI systems using LLMs, with hands-on experience in RAG, vector databases, and embedding models.
• Experience with agent frameworks such as LangChain, LangGraph, or PydanticAI, and with multi-agent systems or tool-using LLMs.
• Experience with LLM evaluation, observability, and cost optimization.
• Expertise in Python and ML frameworks including scikit-learn, XGBoost or LightGBM, and PyTorch.
• Strong MLOps experience covering model versioning, CI/CD for ML, monitoring, and drift detection; hands-on experience with AWS, Azure, or GCP.
• Strong communication and stakeholder management skills.

Nice to have

• Hands-on experience fine-tuning LLMs, including parameter-efficient techniques such as LoRA or QLoRA.
• Contributions to open-source AI/ML projects or applied research experience in machine learning, NLP, or LLMs.

Culture & Benefits

• Hybrid workplace in Cairo, Egypt.