About the Role
About Tailscale
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.
Job Description
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.
Key Responsibilities
- 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.
- 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.
- 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.
What We Are Looking For
- 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.
- A balanced approach to using AI effectively and safely.
- Comfort with ambiguity and self-directed prioritization on a small, still-forming team.
- Product or systems thinking.
Nice to Have
- Prior experience in developer experience, platform engineering, or internal tooling.
- Experience evaluating or benchmarking LLMs and coding agents.
- Experience with a systems language such as Go or Rust, in addition to Python.
- Background in security or code-review practices.
Requirements
Professional software engineering
5+ years of professional software engineering experience is required.
AI coding tools fluency
Genuine, daily, hands-on fluency with modern AI coding tools is essential.
Internal tools experience
Experience building and shipping internal tools or developer-facing automation is necessary.
Communication skills
Strong written and verbal communication and internal advocacy skills are important.
Nice to Have
Prior experience in developer experience, platform engineering, or internal tooling is a plus.
Experience evaluating or benchmarking LLMs and coding agents is beneficial.
Experience with a systems language such as Go or Rust, in addition to Python, is advantageous.
A background in security or code-review practices is helpful.