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), 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 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 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 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. 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.