Exponential Engineering Head

The Mission

As the Exponential Engineering Head, your mission is to drive engineering transformation augmented by AI. You are expected to decouple headcount from high-velocity software engineering metrics. In this role, you aren’t just managing people; you are architecting an AI-augmented engineering engine. You will be responsible for building the organizational capabilities to leverage Frontier AI tools, transforming the software development lifecycle (SDLC) into a high-leverage system where engineers act as system architects and AI agents handle the heavy lifting.

Key Responsibilities

• AI Strategy & Tooling Orchestration: Design and implement a frontier-first AI roadmap. You will curate and deploy a cutting-edge stack (e.g., Factory AI Cursor, Windsurf, Claude Code) to automate research, requirements planning, routine coding, documentation, testing and deployment.
• Exponential Productivity Scaling: Transition the team from linear output to exponential gains. You will redefine “Engineering Excellence” by measuring AI-driven velocity, aiming for a 5x–10x increase in deployment frequency and feature throughput.
• Frontier Capability Building: Act as the lead “Architect of Workflow.” You will build internal frameworks for Agentic Workflows, where AI agents manage PR reviews, bug triage, and automated refactoring with minimal human intervention.
• Talent Transformation: Evolve the engineering culture. You will mentor senior engineers to become “Prompt Architects” and “AI Orchestrators,” ensuring the team remains at the bleeding edge of AI-assisted reasoning and complex problem-solving.
• AI-Native Quality & Governance: Establish the “Safety Net” for high-speed output. You will implement AI-driven testing (e.g., QA Wolf, Mabl) and security guardrails (e.g., Snyk AI) to ensure that increased speed does not result in technical debt or security vulnerabilities.
• Strategic ROI Tracking: Define and report on the ROI of AI Augmentation. You will use insights from platforms like LinearB or Zenhub AI to visualize productivity gains and adjust strategies based on real-time engineering data.

The “Exponential” Tech Stack

The Director is expected to have deep proficiency in (and provide training for) the following AI tool categories. The toolsets are exemplar and not exhaustive or prescriptive.

• AI Development Environments: Cursor, Windsurf, GitHub Copilot Enterprise.
• Agentic Coding & CLI: Factory AI, Claude Code, OpenDevin.
• Automated QA/DevOps: QA Wolf (for self-healing tests), Harness (for predictive deployments).
• Security & Compliance: Snyk AI, GitHub Advanced Security.
• Engineering Intelligence: LinearB, Zenhub AI (for AI-powered sprint and health metrics).

Qualifications

• Engineering Leadership: 10+ years in engineering, with 5+ years leading high-growth teams. Proven experience in a “Force Multiplier” role. Proven experience in engineering transformation and a high performance culture.
• AI Fluency: Expert-level understanding of frontier AI models, AI based software engineering tools and their application. You should be able to demonstrate how you’ve used AI to solve a complex architectural problem.
• Architectural Depth: Deep knowledge of cloud-native systems (AWS/GCP), microservices, and—crucially—how to build AI-ready codebases (clean, well-documented, and modular).
• Education: Bachelor’s/Master’s in CS or equivalent; specific certifications or deep-dive projects in AI/ML are a significant plus.