Software Engineer, AI Enablement

Tailscale is building the new Internet by delivering software that makes it easy to securely interconnect people and their devices, no matter where they are. From hobbyists to multinational corporations, teams of every size use Tailscale each day to protect their networks, share access to internal tools, and more. We're building a future for the Internet that's easy, sensible, and safe, like it used to be. Founded in 2019 and fully distributed, we're backed by Accel, CRV, Insight, Heavybit, and Uncork Capital.

We're seeking a talented and motivated full-time Software Engineer, AI Enablement to help Tailscale's engineering organization get the most out of AI-assisted development. You'll join a small, high-leverage team reporting to our co-founder, working alongside our first AI enablement engineer to build the tools, workflows, and practices that help every engineer at Tailscale build faster and more safely with AI. This is a foundational role — you'll have real latitude to shape what AI enablement means here as we scale, with direct visibility into how the whole engineering org adopts these tools.

• Partner with engineering leadership, our co-founder and members of technical staff to define Tailscale's internal AI-enablement priorities and roadmap.

• Work with the team that’s building Aperture by Tailscale – our AI gateway that we both use internally and provide as a product.

• Build, maintain, and iterate on internal tools, workflows, and shareable practices (skills, development environments, internal tooling) that help engineers use coding agents like Claude Code, Codex, OpenCode, and Pi more effectively.

• Evaluate new AI models, agents, and tools, and make clear recommendations on what to adopt and why.

• Work directly with both engineering and non-engineering teams across the company to find high-leverage opportunities to apply AI to their day-to-day work — this is a support/enablement function, not a standalone product team, so success means other teams shipping faster because of what you've built.

• Develop infrastructure, guardrails, review practices, and documentation for the safe, secure use of AI-generated code.

• Act as an internal advocate for effective AI practices — through documentation, internal talks, and hands-on coaching — meeting teams where they are rather than mandating a single tool or workflow.

• Track adoption and measure the real impact of AI tooling on engineering velocity and quality, and report back to leadership.

• Expect the day-to-day to span hands-on building, internal teaching/evangelism, and prioritization — on a team this size, you'll move between all three regularly.

• 5+ years of professional software engineering experience

• Genuine, daily, hands-on fluency with modern AI coding tools (Claude Code, Codex, Pi, or similar) — real power-user experience, not occasional use

• Experience building and shipping internal tools or developer-facing automation

• Strong written and verbal communication and internal advocacy skills — comfortable teaching, writing, and influencing engineers at very different comfort levels with AI tooling

• A balanced approach — trying to get people to use AI effectively and safely where appropriate. We don't have an 'AI mandate'; we believe that if we make AI both easy to use and safe, people will choose to use it when appropriate

• Comfort with ambiguity and self-directed prioritization on a small, still-forming team

• Product or systems thinking — able to identify and prioritize