Lead AI Engineer
Real Estate
About the role
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., gr…