⌘About Timeleft Timeleft is a social app that brings strangers together. We match people into groups of 6 and send them to restaurants, cafés, and bars for dinners, drinks, coffees, and runs. Every week, 150,000+ people use Timeleft across 200+ cities in 52 countries.

We're 100 employees — and the product, the operations, and the pace are scaling faster than the team. That means every department — HR, Support, Ops, Finance, Marketing — is running into the same wall: too much manual work, not enough hands. We need someone to tear those walls down.

That's where you come in. ⌘The role You will sit within the Tech team and serve as the bridge between engineering and every other department at Timeleft. Your job is to identify, design, and ship internal automations that eliminate manual work across the company — HR onboarding flows, support ticket classification, ops reporting pipelines, finance reconciliation, and whatever else is burning time.

This is not a "connect two Zaps together" role. We expect deep, hands-on experience with AI-native development tools — Claude Code, Cursor, MCP servers, agentic workflows, scheduled AI tasks, and live interactive artifacts. You'll build real systems that use LLMs as core infrastructure, not just sprinkle AI on top.

You should be someone who has already built things with these tools and can show us what you've shipped. You'll work at the intersection of vibe-coding, no-code/low-code platforms, and lightweight scripting — building the internal tooling and workflows that make Timeleft run faster.

Key Responsibilities

AI-native development and agentic automation Build and maintain AI-powered workflows using Claude Code, Cowork, MCP servers, and agentic frameworks Create custom Skills and plugins that encode repeatable workflows for non-technical teams Design live artifacts and interactive dashboards that pull real-time data from internal tools via MCP connectors Set up scheduled AI tasks for recurring work — weekly reports, data quality checks, digest generation, Slack summaries Evaluate, prototype, and ship LLM-based automations: classification, extraction, summarization, drafting, routing Build and connect MCPs to integrate internal systems (Google Workspace, Slack, Notion, Jira, etc.) into AI workflows Cross-functional automation delivery Partner with HR, CX, Ops, Finance, and other teams to identify and prioritize automation opportunities Own the full lifecycle: intake → design → build → deploy → maintain Examples: automated employee onboarding (Google Workspace provisioning, Slack invites, welcome emails), support ticket auto-classification and routing, automated reporting and alerting No-code / low-code solutions Use platforms like Make (Integromat), Zapier, n8n, or Retool where they're the fastest path to value Know when no-code is the right call and when you need to write actual code Build internal dashboards and admin tools using low-code frameworks Vibe-coded applications Rapidly prototype and ship internal tools using AI-assisted development (Claude Code, Cursor, Copilot) Write Python/TypeScript/SQL scripts for data pipelines, integrations, and automation Comfortable with pragmatic code that solves the problem — ship fast, iterate based on feedback, harden what sticks Documentation and handoff Document every automation so non-technical stakeholders can understand what it does, when it runs, and who to contact when it breaks Train team members on self-service tools where appropriate ⌘Expected Outcomes Automations shipped per quarter: 3–5 meaningful cross-functional automations delivered and running in production Time saved: Measurable reduction in manual hours for partner teams (target: 20+ hours/week saved across the org within 6 months) Reliability: Automations with clear alerting and fallback paths Stakeholder satisfaction: Positive feedback from internal "clients" (HR, CX, Ops)

Automation Engineer