This is a hybrid role that will sit out of our San Francisco office. Hybrid in-office Tuesdays and Wednesdays of each week.
We are looking for a hands-on builder to lead our ‘AI for Work’ efforts. This role is focused exclusively on internal operations — there is no external product work. Reporting to the Director of AI Strategy and Enablement, you will embed directly within our business functions, map and reimagine how work gets done, and build the AI agents, automations, and internal tools that make our teams dramatically more efficient.
You will execute without a dedicated engineering partner. The right candidate has shipped Claude-powered workflows, agents, and automations in a professional context and can do it again here — independently, scrappily, and fast. Beyond building, you will help each function develop the capability to identify and build their own AI solutions over time.
- Discover & diagnose: Embed with business teams across functions to map end-to-end workflows, surface high-impact automation opportunities, and redesign work from first principles — not just automate existing steps.
- Build: Independently design, build, and deploy Claude-powered agents, automations, and internal tools that eliminate repetitive work and improve output quality and consistency.
- Measure: Establish baselines before every intervention; define and track the right business metrics for each function (e.g. time saved, error rate) to validate real impact, not just adoption
- Enable: Train and enable non-technical teams to identify, scope, and eventually build their own automations — building durable capability within functions, not dependency on this role.
- Influence: Serve as a trusted translator between business problems and technical solutions; partner with senior leaders to align automation priorities with company OKRs and drive change with skeptical or resistant stakeholders.
- Scale: Build reusable patterns and playbooks so successful automations in one function can be adapted and scaled across the organization.
- Experience: 2+ years of hands-on experience building AI agents, automations, and internal workflows professionally — including direct, independent work with Claude (Claude Code, Claude API, Claude Skills, or agentic frameworks built on Claude).
- Industry : Marketplace or Gig economy company (e.g. Airbnb, Lyft, Doordash) or high-growth startup strongly preferred.
- Business partnership: Proven ability to embed with non-technical business teams, run structured discovery, and translate workflows into automation opportunities — including the judgment to know when AI is not the right answer!
- Enablement: Track record of building AI capability in others, not just building for them.
- Stakeholder influence: Track record of moving skeptical or resistant stakeholders from hesitation to adoption; strong communicator who can present clearly to senior leaders and frontline teams alike.
- Impact measurement: Data-driven approach to measuring impact – comfortable defining baselines and metrics from scratch for a given workflow, and quantifying results in business terms.
- Technical depth: Builder-level fluency with LLMs and agentic frameworks, demonstrated through production work — not chat-only prototyping. Should surface sound technical judgment unprompted: model selection, caching strategy, human-in-the-loop design, and awareness of reliability issues. Ability to forecast costs and manage token costs.
- Builder mindset: Scrappy, self-directed execution style. Comfortable operating without dedicated engineering support in a fast-paced, resource-constrained environment.
At Taskrabbit, our approach to compensation is designed to be competitive, transparent, and equitable. Total compensation consists of base pay + bonus + benefits + perks. The base pay range for this position is $175,000 - $225,000.
This range is representative of base pay only, and does not include any other total cash compensation amounts, such as company bonus or benefits. Final offer amounts may vary from the amounts listed above and will be determined by factors including, but not limited to, relevant experience, qualifications, geography, and level.