Vice President of Engineering

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), Tech Jays (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:
Dev Ops/infrastructure, data, security awareness, regulatory compliance context.

Must-Have Background (Non-Negotiables)

• High-tech industry experience at a senior leadership level - CTO o 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 Lang Chain, Lang Graph, 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 stable, 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.

Deal breakers — 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.