Head of Engineering - Stealth AI Logistics Billing Platform

UP.Labs

About The Position

UP.Labs is hiring a hands-on Head of Engineering for a stealth startup in the logistics space, building an AI-powered platform focused on freight billing, revenue integrity, and cash-flow automation. Freight billing today is fundamentally broken. Complex contracts, fragmented systems, and manual, error-prone workflows lead to disputes, revenue leakage, delayed payments, and significant overhead. This company exists to change that by unifying fragmented data into a single source of truth, validating invoices automatically, and identifying discrepancies in real time, turning revenue chaos into predictable outcomes. As the first engineering leader, you will own the technical foundation end-to-end: architecture, data infrastructure, AI integration, and team building. You’ll stay hands-on early, build from first principles, and define the long-term technical direction as the platform scales to enterprise adoption. You’ll also have access to the UP.Partners ecosystem, a world-class team across product, engineering, design, analytics, marketing, legal, talent, finance, and venture capital - to help accelerate execution.

Requirements

8+ years of software engineering experience, including 4+ years leading small, high-impact teams.
Strong backend or full-stack background with the ability to remain hands-on.
Proven experience building and scaling B2B SaaS platforms with complex data pipelines and system integrations.
Deep knowledge of cloud architecture, CI/CD pipelines, observability, and distributed systems.
Experience working with AI/ML systems (e.g., LLMs, rules engines, optimization or validation models).
A technical leader who thrives at the intersection of data, AI, and enterprise SaaS.
Deeply hands-on comfortable writing code, reviewing PRs, and making architectural tradeoffs.
Experienced integrating complex, messy enterprise systems and normalizing inconsistent data.
Fluent in building platforms that combine data infrastructure, applied machine learning, and workflow automation.
A collaborative partner who works seamlessly with product, data science, and business stakeholders.
Comfortable operating in ambiguity and scaling systems and teams from 0→1 and beyond.

Nice To Haves

Familiarity with enterprise finance, billing, or revenue systems is a strong plus.
Experience leading or managing distributed (nearshore/offshore) engineering teams.
Background in logistics, supply chain, or fintech is helpful but not required.

Responsibilities

Lead and grow the engineering function, balancing hands-on development with technical leadership and team building.
Architect and own the core platform, including: Data ingestion and normalization pipelines AI/ML and rules-based validation layers Scalable, secure enterprise infrastructure
Build and maintain deep integrations with enterprise systems such as TMS, ERP, billing platforms, and other operational data sources.
Partner closely with Product and Data Science to translate complex, real-world billing workflows into intelligent, automated solutions.
Design systems that support invoice validation, discrepancy detection, exception handling, and auditability.
Establish best practices around security, CI/CD, observability, testing, and documentation suitable for enterprise finance and operations teams.
Define the technical vision for AI-driven automation, explainability, and closed-loop resolution workflows.
Manage and mentor distributed contributors (including nearshore/offshore teams), building a high-trust, high-output engineering culture.
Deliver rapid MVP iterations while laying a durable foundation for enterprise scale and reliability.