Overview

Data Platform Architecture

Responsibilities

• • Data pipelines and distributed data processing • Data lake / lakehouse architectures • Streaming and real-time data processing • Large-scale analytics platforms
• • ML pipelines and feature stores • Model training and deployment • ML model monitoring and lifecycle management
• • Large Language Models (LLMs) • Retrieval-Augmented Generation (RAG) • Vector databases and embedding systems • AI agents and copilots • Prompt engineering and LLM orchestration frameworks

Qualifications

• • Experience leading Data Engineering or AI/ML Engineering teams. • Strong background in large-scale data systems. • Experience building production machine learning systems. • Good
• understanding of Generative AI and LLM-based applications. • Experience designing scalable data and AI platforms. Preferred Qualifications • Experience building AI-powered enterprise platforms. •
• Experience integrating GenAI features into production systems. •
• Experience with large-scale data environments. •
• Familiarity with geospatial or location intelligence data. Leadership Expectations The Head of Data & AI/ML Engineering will: • Define the data and AI strategy for the company. • Build scalable data platforms and AI infrastructure. • Enable product teams to leverage data, ML, and GenAI capabilities. • Drive innovation through AI-powered product development.