Lead AI Engineer

Nawy Real Estate Open · verified Nov 1, 2026

On-site Cairo Senior AI Engineering

At a glance

Senior AI Engineering role at Nawy Real Estate. Cairo.

Pay not stated AI Engineering salary

RoleAI Engineering

SenioritySenior

LocationCairo

WorkplaceOn-site

PostedOct 19, 2026 · 13d ago

Role brief

aimlroles summary, based on the employer's posting.

What you'll do

Drive AI projects from early experiments through launch, then improve their performance in production
Shape system designs for data pipelines, model serving, vector search, retrieval-augmented generation and agent workflows
Build and guide classical prediction, ranking, recommendation and scoring models alongside LLM-based products
Choose between conventional machine learning, language models, fine-tuning or blended approaches using cost and performance trade-offs
Set engineering practices for testing, deployment, monitoring and model evaluation while mentoring engineers and reviewing their work

What you bring

At least six years in AI, machine learning or data science, plus a degree in computing, engineering or a related area
At least one year leading engineers, including responsibility for hiring and people management
A track record taking classical ML models and LLM-based systems into production, including retrieval, vector databases and embeddings
Strong Python and ML framework skills, backed by MLOps experience and hands-on work with a major cloud platform
Experience with agent frameworks such as LangChain, LangGraph or PydanticAI, plus LLM evaluation and cost control

Who this fits

This senior, hands-on lead role suits someone who can guide engineers while still designing and delivering production AI systems. The position is onsite in Cairo, Egypt.

From the employer

Description

We are looking for a Lead AI Engineer with 6+ years of experience to lead the technical development and delivery of AI solutions. You will provide hands-on technical guidance to a team of AI engineers and deliver both classical ML and GenAI solutions to production. You will work closely with product, data, and business teams to translate business needs into reliable, scalable, and impactful AI solutions.

Responsibilities

Lead the end-to-end technical implementation of AI/ML projects, from prototyping and experimentation to production deployment and optimization.
Design and review the architecture of AI systems, including data pipelines, model serving, vector databases, RAG systems, and agentic workflows.
Guide the development of classical ML models (prediction, ranking, recommendation, scoring) and GenAI solutions (RAG, AI agents, LLM applications).
Evaluate and select appropriate approaches for each problem, including classical ML, LLMs, fine-tuning, or hybrid solutions, based on accuracy, cost, performance, and maintainability.
Provide hands-on technical guidance, conduct code and architecture reviews, and mentor AI engineers.
Implement and maintain engineering best practices for code quality, testing, CI/CD, MLOps, model evaluation, and monitoring.
Ensure production AI systems are reliable, scalable, secure, and cost-efficient, applying appropriate safeguards for data privacy and responsible AI.
Collaborate with product, data, and engineering teams to translate business requirements into technical solutions and communicate technical trade-offs to stakeholders.
Troubleshoot complex technical challenges, optimize system performance, and contribute to the development of reusable AI components.

Requirements

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

Preferred Qualifications

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

AI Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

AI Engineering

Find me work

By the team behind aimlroles.

Find me work