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.
Skills Required
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 6+ years of experience in AI, machine learning, or data science roles
- 1+ years leading a team of engineers, including hiring and people management
- Experience building and deploying classical machine learning models, including prediction, ranking, recommendation, scoring, or time-series forecasting
- Strong knowledge of feature engineering, model validation, and experiment design, including A/B testing
- Experience designing and deploying generative AI systems using large language models
- 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
- Expertise in Python and machine learning frameworks including scikit-learn, XGBoost, LightGBM, or PyTorch
- Strong MLOps experience, including model versioning, ML CI/CD, monitoring, and drift detection
- Hands-on experience with AWS, Azure, or GCP
- Strong communication and stakeholder management skills
- Experience with multi-agent systems or tool-using LLMs
- Hands-on experience fine-tuning LLMs using parameter-efficient techniques such as LoRA or QLoRA
- Contributions to open-source AI/ML projects or applied machine learning, NLP, or LLM research experience
What We Do
An end to end platform providing a seamless experience for prospective buyers, sellers & investors in the real estate space. We are a tech-based information & services hub with multiple arms that tackle every step of our clients journey from searching for a home, to buying, selling, consulting and/or investing in properties on a fully immersive digitized platform. Using machine learning and tailored algorithms that foresee & learn customer demands properties are recommended that better suit their needs. The ease of online navigation, the ability to compare different properties and filter according to personal interests allows customers malleability and short search times. Our Nawy Now service allows customers to move in and pay later with reasonable payment plans. This program tackles the adversity of finding ready to move homes by providing a wide array of competitively priced properties with up to 10 year installment plans.
