Technical AI Engagement Lead

Responsibilities:

• Take the cascade load off the CTO by turning their vision into team-level discipline: specs, rules, review standards, reusable skills, and onboarding of the next circle of engineers.
• Run the diffusion loop between companies: detect what already works in one team, validate direction and risks, package it into a reusable artifact, transfer it to the rest, and measure against objective criteria.
• Operate the rhythm: bi-weekly validation calls, monthly cross-company demo meets, per-company status board, and monthly steering sync with the group CTO.

Requirements:

• Hands-on daily fluency with agentic coding stacks: Claude Code, Cursor, Codex, including MCP servers, skills, sub-agents, and spec-driven development.
• AI architecture expertise: LLM gateways/proxies, cost and error attribution, local-LLM trade-offs, and in-region deployment patterns.
• Engineering-leadership credibility at tech-lead / AI-architect / head-of-engineering level, able to review real code, pipelines, and specs with senior engineers.

Skills:

• Facilitation of technical sessions: live demos, validation calls, hands-on workshops with real repos.
• Packaging: turning a working practice into an artifact that another team adopts without the author in the room.
• Knowledge Engineering measurement in the AI era: DX Core 4 / DORA, AI-impact metrics, and quality guardrails for AI-generated code.