Engineering Manager, Strategic Projects

Tailscale Tailscale · Enterprise · Remote · Strategic Projects

Engineering Manager for a strategic projects team focused on AI-native initiatives, including an identity-aware LLM gateway and heavy use of coding agents. The role involves managing senior engineers, partnering with leadership and customers to develop prototypes and reference architectures, and setting standards for AI tool usage in development.

What you'd actually do

  1. Manage a talented, senior team of experienced engineers in a growth-stage startup.
  2. Drive business outcomes measured by adoption of new platform primitives, customer integrations landed, and influence on Tailscale's roadmap.
  3. Make major design decisions on prototypes that often graduate into production surface area, and own the quality bar for the team's externally-visible artifacts (reference architectures, open source, talks, customer integrations).
  4. Set the bar for how this team uses AI coding tools: which agents and workflows the team adopts, what review and security practices wrap around agent-generated code, and how the team sustains a fast cadence without lowering the production bar.
  5. Hire, nurture, and oversee engineers while fostering a fun, creative, and inclusive atmosphere, including healthy conflict and a culture of candid, kind feedback.

Skills

Required

  • Substantial experience managing and mentoring engineering teams: performance, career development, hiring, and culture
  • Experience developing in Go, the primary language across Tailscale's stack and this team's prototypes
  • Heavy daily use of coding agents (Claude Code, Cursor, or similar) and LLMs in your engineering workflow, with a point of view on where they accelerate work, where they fail, and how to wrap them in review and security practices that hold the production bar. Able to coach engineers on your team to operate the same way
  • Comfort with exploratory, customer-facing engineering: translating customer conversations into prototypes and reference designs
  • Comfort with the cadence of a strategy team at an early-ish startup: priorities shift with market signal, prototype-to-production timelines are short, and the bar on what ships stays high regardless

Nice to have

  • Building applications on top of LLMs and agentic systems (not just using them as dev tools)
  • Networking background (L4-L7 connectivity, browser and DNS behaviors), and familiarity with Tailscale itself
  • Identity infrastructure background: IdP platforms, identity sync/provisioning, directory services, and protocols (OAuth, OIDC, SAML, SCIM); access control models (RBAC/ABAC), session management, MFA, passwordless auth
  • Leading teams whose output is publicly visible (open source, devrel, reference implementations) and validating prototype code for production alongside security teams

What the JD emphasized

  • Heavy daily use of coding agents (Claude Code, Cursor, or similar) and LLMs in your engineering workflow, with a point of view on where they accelerate work, where they fail, and how to wrap them in review and security practices that hold the production bar. Able to coach engineers on your team to operate the same way
  • Comfort with the cadence of a strategy team at an early-ish startup: priorities shift with market signal, prototype-to-production timelines are short, and the bar on what ships stays high regardless

Other signals

  • AI-native team
  • coding agents heavily as a force multiplier
  • AI infrastructure, agentic tooling
  • identity-aware networking
  • shippable POCs and reference architectures
  • AI coding tools