Head of Tech (Engineering & AI)

Portcast is a venture-backed, Singapore-based logistics technology startup building a real-time transportation visibility platform for global supply chains. We help shippers, manufacturers, and logistics service providers turn data into decisions and decisions into measurable business impact.

Our platform goes beyond visibility. Portcast enables action at scale by surfacing the right risks early, helping teams prevent detention and demurrage, accelerate exception management, and close invoices faster with built-in evidence. We turn visibility into outcomes: reduced costs, improved operational control, and more predictable supply chains.

Founded in 2018 and backed by leading technology investors, we are building for an industry at a critical inflection point of digital transformation. Our team of software engineers, data scientists, and logistics experts is on a mission to make supply chains not just visible, but decisively actionable end-to-end.

We’re looking for a Head of Tech (Engineering & AI) to lead our engineering, ML/DS, and analytics teams while staying close to architecture and execution.

This role will lead and manage the Engineering team, ML/Data Science team, and Data Analytics team. You’ll drive how we build, how we use data and AI, and how our systems scale as the company grows.
We’re looking for a strong technical leader who thinks from first principles, makes clear decisions, and stays close to the technology. Someone who can step into complex problems, break them down clearly, and guide teams toward practical, scalable solutions.

You’ll work closely with the CEO, Product, Sales, and Customer teams to translate real customer problems into systems, tools, and AI capabilities that drive outcomes, value to our customer and company revenue, not just features.
This is not a pure management role. It requires strong technical judgment, comfort operating across engineering and data, and the ability to lead through both direction and execution. You’ll set the technical bar, strengthen how teams work together, and ensure engineering, ML, and analytics move as one cohesive capability supporting the business.