Vice President Developer Operations Jobs in Riverside, CA

Vice President of Engineering – Fractional SVP Engineering – Generative AI

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.

They report to the CEO and work 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: built with LLMs, agentic systems, or AI tooling in the last 12–18 months; hands‑on experience using up‑to‑date 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 secure, 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.