# Software Engineer, AI Enablement

**Company:** [Tailscale](https://hotfix.jobs/companies/tailscale)
**Location:** Remote
**Role:** DevOps / SRE
**Salary:** $163k – $226k/yr
**Experience:** 5+ years
**Skills:** ai coding tools, Claude Code, Codex, LLMs, Python, Go, Rust, internal tooling, developer experience, Platform Engineering, security practices, Code Review
**Posted:** 2026-07-24

> Software Engineer building internal AI enablement tools, workflows, and practices at Tailscale to help engineers adopt AI coding agents like Claude and Codex more effectively and safely. Requires 5+ years software engineering experience and daily hands-on fluency with modern AI tools.

## Job Description

## 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 — 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.

## Requirements
- 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 high-leverage opportunities, not just execute a pre-set roadmap

## 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 — helpful for reasoning about AI/agent-generated code, though you don't need to be a security engineer
- Experience in developer relations, technical evangelism, or customer-facing developer advocacy — the same skills that make someone effective in external DevRel translate well to driving internal AI adoption
- Technical project management experience

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