AI Enablement Engineer — Build Internal AI Tools

Promptcube3; United Kingdom; Teletrabalho; GBP 129 000 - 179 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Health insurance

Dental coverage

Vision coverage

Remote-first

Annual retreat

Retirement contributions match

Resumo da oferta

Tailscale is seeking a talented Software Engineer, AI Enablement to help accelerate AI-assisted development across the engineering organization. You will shape the internal AI-enablement roadmap, build tools and workflows, and establish guardrails to ship safe, AI-generated code.

You will partner with leadership and teams to drive adoption of Aperture by Tailscale, evaluate new models, and measure impact on velocity and quality while empowering engineers to work more effectively with AI.

Qualificações

• 5+ years of professional software engineering experience.
• Genuine, daily, hands-on fluency with modern AI coding tools (Claude Code, Codex, Pi, or similar).
• Experience building and shipping internal tools or developer-facing automation.
• Strong written and verbal communication and internal advocacy skills.

Responsabilidades

• Define and drive the internal AI-enablement roadmap with engineering leadership.
• Collaborate on building Aperture by Tailscale, the AI gateway used internally and as a product.
• Develop tools and practices to deliver value from AI-assisted coding and evaluate new models/tools.
• Track adoption and measure impact on velocity and quality; report to leadership.

Conhecimentos

AI tooling

Software engineering

Internal tooling

Communication

Prioritization

Ferramentas

Go

Rust

Python

Descrição da oferta de emprego

Tailscale is seeking a talented Software Engineer, AI Enablement to help accelerate AI-assisted development across the engineering organization. You will shape the internal AI-enablement roadmap, build tools and workflows, and establish guardrails to ship safe, AI-generated code.

You will partner with leadership and teams to drive adoption of Aperture by Tailscale, evaluate new models, and measure impact on velocity and quality while empowering engineers to work more effectively with AI.