Head of Engineering

About this role

Head of Engineering - Seed-stage startup

About our client

Our client is building the operating system for global logistics — turning fragmented operational and document-based data into a single source of truth powered by data and AI.

This is a complex, real-world B2B domain where systems must be reliable, scalable, and deeply integrated with external partners. As the company grows, engineering quality, velocity, and ownership will define the next chapter.

The role

We are looking for a Head of Engineering to lead, scale, and elevate the engineering organisation while staying deeply connected to the product, the business, and real customer problems. This is not a process-only role. This is a builder–leader role.

You’ll own engineering end-to-end — people, systems, quality, and delivery — and lead by context, clarity, and example.

What you’ll do

- Own delivery across Backend, Frontend, Data, and Infrastructure

- Ensure teams ship reliable, scalable systems used for critical logistics operations

- Balance speed and quality in a high-stakes, real-world environment

- Set technical direction and guide architecture decisions across distributed, integrations-heavy systems

- Build and scale a high-performing team with strong ownership and accountability

- Partner closely with Product, Data/AI, Partnerships, and Leadership

What we’re looking for

- 8+ years of software engineering experience

- Experience leading engineering teams in startups or fast-growing product companies

- Background in complex, real-world domains (B2B, logistics, fintech, platforms, data-heavy systems)

- Strong experience with backend-heavy systems

- Experience running production systems on AWS

- Comfortable reviewing architecture and code, even if not coding daily

Tech stack context (experience leading teams in a stack like this):

- Backend: Kotlin, Python

- Data: PostgreSQL, MongoDB / NoSQL

- Infrastructure: AWS, containers, CI/CD, observability

- Integrations: REST, async pipelines, SFTP

- Data & AI: large-scale ingestion, OCR, LLM-powered workflows in production