Breakmark

Head of Engineering

2mo ago
USAHeadRemote
Breakmark

Head of Engineering

2mo ago
USAHeadRemotebackendfrontenddatainfrastructurearchitecture

Lead and scale the engineering organization for a seed-stage startup focused on logistics operating systems, managing teams and technical direction.

Responsibilities

  • 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.

Other

  • 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.
  • 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
  • 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
  • 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