Vice President of Engineering (Moncton)

Vice President of Engineering

Project: Fractional SVP Engineering

Technologies: Generative AI

Seniority: Senior

Role Overview

The Fractional SVP Engineering will serve as the de‑facto head of engineering during a critical transitional window, with a strong likelihood of transitioning to a full‑time permanent role for the right candidate.

This person reports to the CEO and works closely with the Chief Product Officer and Head of Data/AI.

They will be the senior technical voice in the room – able to speak credibly to the board, to engineers, and to external vendors.

Core Responsibilities

• Establish engineering leadership, cadence, and accountability from day one.
• Own the technical vision and execution roadmap across both product platforms (landing page builder and CRM).
• Drive adoption of structured engineering processes (Scrum/Agile done properly) – lead by example, not committee.
• Manage and align relationships with external vendors: Kaylent (AWS/AI partner), TechJays (agentic dev), and any future partners.
• Evaluate and shape the post‑restructuring engineering team – retain, develop, and recruit AI‑forward talent.
• Provide technical credibility with engineers: this person must be respected for what they know and have built, not just their title.
• Bridge business strategy and technical execution – translate customer impact and commercial goals into engineering priorities.
• Cover the full CTO remit where needed: DevOps/infrastructure, data, security awareness, regulatory compliance context.

Must‑Have Background (Non‑Negotiables)

• High‑tech industry experience at a senior leadership level – CTO or VP Engineering track record owning architecture, defining strategy and leading and retained 30 or more engineers.
• Proven track record leading engineering organizations through transformation – not just steady‑state management. Post‑restructuring transformation experience required.
• Deep, current fluency in AI‑first development: has built with LLMs, agentic systems, or AI tooling in the last 12–18 months. Hands‑on experience using modern LLM frameworks such as LangChain, LangGraph, RAG pipelines, agentic workflows.
• Experience in SaaS environments, ideally having led or witnessed a product org redefine itself around AI.
• Ability to command technical respect from senior engineers – can speak architecture, review code credibly, demonstrate street cred.

What they must bring

• Bias for Action – moves fast, decides with incomplete information, doesn't wait for consensus.
• Results Focus – outcome‑oriented; cares about what ships and what impact it has on the business.
• Customer First – understands that engineering decisions exist in service of the customer and the business.
• High‑Velocity Decision Making – can cut through ambiguity and commit.
• Individuality – brings a distinct point of view; not a follower of the room.
• Ability to build buy‑in – earns trust with engineers by being credible, not by being popular.

Context & Situation

Understanding this context is critical for assessing candidate fit. This is not a reliable, steady‑state role. The right person will thrive in it precisely because of the challenge.

Where the organization is today

• The Head of Engineering departed end of March 2026 after a planned transition.
• The engineering org (~55 people) has been operating below velocity expectations for 18+ months.
• A restructuring is underway: approximately 20 engineers will be released; high performers and AI‑forward builders are being retained with stay bonuses.
• The incoming SVP will not be expected to lead the layoffs – the CEO will manage that directly – but they will walk into the post‑restructuring environment and must be equipped to rebuild trust, morale, and momentum quickly.

Dealbreakers – what will disqualify a candidate

• No sense of urgency. This role requires a Driver.
• Ego that prevents collaboration or creates friction with leadership peers.
• Strategic blindness – must understand the commercial and operational impact of engineering decisions.
• Avoidance of accountability or difficult conversations.
• Unfamiliarity with AI‑first development as a practice, not just a talking point.

Areas of Flexibility

The client is open on specific vertical/domain experience, exact company size, and whether the candidate comes from a pure engineering or engineering‑adjacent background – provided they can demonstrate the non‑negotiables above.