NetBox Labs is crossing a threshold: from a set of strong teams to a coordinated multi-team organization.
We are evolving from a single product into a multi-product platform, operating across both SaaS and on-prem delivery models. We are standardizing shared foundations across teams while continuing to ship.
Today, the CTO carries both strategic and operational responsibility. We are creating this VP of Engineering role to own day-to-day engineering execution — delivery, people development, and cross-team coordination — so the CTO can focus on strategy. The goal is to build a system that reliably turns strategy into shipped product.
At the same time, the company is committing to a step-function shift toward AI-native engineering. This is not incremental optimization. It is a redefinition of how software is built. This is the company’s top organizational priority, and it is already underway.
You will not be starting from scratch. You will be joining a system mid-transformation and expected to accelerate it.
Scrappy execution
You are comfortable making pragmatic progress without perfect structure, complete resourcing, or full alignment. You unblock teams by simplifying problems, making tradeoffs explicit, and moving work forward with the resources available.
You create momentum in imperfect conditions, tightening the system over time rather than waiting for it to be designed upfront.
The engineering organization
You will lead three engineering directors and their teams. You are accountable for leadership quality, team performance, and output.
Execution system
You own how work gets done: planning, cycles, release coordination, and cross-team execution. The core challenge is across teams: coordinating multiple products, shared platform work, and dual delivery models.
You will shape team boundaries and interfaces so teams can move quickly with minimal coordination overhead. This includes clarifying ownership, reducing cognitive load, and defining clean contracts between teams.
AI-native practices are a core part of the execution system: spec-driven development, AI-assisted implementation and review, and faster iteration cycles with stronger verification and operational rigor.
Quality and operational discipline
You own the systems that protect velocity: CI/CD, testing strategy, reliability, and incident response.
We are investing in an AI accountability model: progressively delegating work to AI systems with guardrails based on risk. Your role is to operationalize this — not as a concept, but as daily engineering practice.
People and performance
You own hiring, performance management, and leadership development.
You will partner with the CTO on org design as the company scales.
Technical direction
The CTO and a principal engineering group own architecture and long-term technical strategy.
You are expected to engage and challenge, but your primary responsibility is execution against that direction.
Product roadmap
Product reports separately to a VP of Product.
You will partner closely, but you do not own prioritization.
Engineering delivers predictably across multiple products and delivery models without executive intervention
Directors independently run high-functioning teams with minimal escalation
Platform (Foundations) investment materially reduces delivery friction and duplication of work
Cross-team coordination no longer blocks major initiatives
AI-native practices measurably improve throughput and/or quality
The CTO is fully out of day-to-day execution management
You are joining mid-flight
Org structure, operating model, and AI practices are all evolving simultaneously.
You will need to quickly distinguish:
What is working and should be reinforced
What is fragile and needs structure
What is wrong and needs to change
AI-native is real, but immature
We have a framework and early adoption, but not consistency.
You will need to push adoption where it creates leverage, constrain it where it creates risk, and build systems that maintain comprehension and quality.
Hybrid SaaS + on-prem is operationally harder
On-prem environments introduce less observability, less control, and slower feedback loops compared to SaaS.
If you default to SaaS-only assumptions, you will break things.
Multiple products, shared foundations
Operating multiple products on shared infrastructure introduces coordination challenges that require deliberate system design. The goal is clear ownership and well-defined interaction patterns so teams can operate independently where possible and collaborate intentionally where necessary.
You inherit leaders to develop
You will inherit a group of engineering directors with diverse strengths and growth areas.
Your role is to help them operate as a cohesive leadership team with clear expectations, strong execution discipline, and shared accountability.
This role emphasizes:
Coaching and support
Clarity of expectations
Consistent follow-through
You will work through these leaders, not around them.
This is not a CTO-in-waiting role. You will not own technical direction, architecture, or long-term technology strategy.
Your mandate is to build and run the execution system that turns that strategy into reality.
Your role is to build a system that scales beyond individual leaders.
You should expect to form strong opinions quickly and act on them within weeks, not months.
Pragmatic operator
You have a bias toward progress. You can move work forward with incomplete information, limited resources, and evolving structure. You know when to invest in process — and when to bypass it to get results.
You simplify, prioritize, and execute rather than waiting for ideal conditions.
Scaled engineering leadership (40–100 engineers)
You have built and run an engineering organization at this size. You know how to introduce structure without slowing teams down.
Execution track record
You have owned outcomes: shipped products, improved delivery systems, and fixed execution failures.
Infrastructure / platform fluency
You can engage credibly with engineers building infrastructure, developer tooling, and systems software.
Manager of managers
You develop leaders. You hold them accountable. You make them better.
AI-native conviction (grounded in practice)
You have hands-on exposure to AI-assisted development and a point of view on how it changes engineering.
Hands-on when needed
You can dive into the work to understand how things actually function — reading code when useful, asking sharp questions, using modern tooling (including AI) to investigate, and helping teams unblock.
We own and solve problems with high attention to detail.
Our open source contributors, users, customers & team are all part of our community. When our community wins, we win.
We prioritize simplicity and think twice before adding complexity
Clear communication helps keep our team aligned and collaborating smoothly.
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