Forward Deployed Engineer

Taskrabbit · San Francisco, California, United States

  • Junior
  • Full-time
  • $175,000 – $225,000
  • Posted 2026-04-30
  • Confirmed live on 25 September 2026

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Job description

About Taskrabbit:

Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more.

At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world.

Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed!

This is a hybrid role that will require two days in-office each week on Tuesdays and Wednesdays at our SF location on 130 Sutter Street.

About the Role

Every business function at Taskrabbit — Marketing, Customer Support, Finance, Operations — is a "customer" with real workflows, real data, and real friction. Your job is to embed with them, scope their use cases, and build the Claude-powered agent, automation, or tool that solves them.

This is an internal-facing role — there is no external customer or product work. Reporting to the Director of AI Strategy and Enablement, you'll operate the way an FDE operates at a high-growth AI company: full ownership of a deployment from discovery through production and direct accountability for whether what you ship actually changes a metric. In most cases you'll own a build end-to-end solo; in some functions you may partner with that team's own subject-matter expert to pair domain depth with technical execution.

We are hiring for engineering depth first. This is not a role for someone whose experience is limited to no-code/low-code automation platforms (Zapier, Make, n8n) without underlying software engineering fundamentals. The bar is: you have personally written, tested, and shipped production code that calls an LLM — ideally Claude — as part of an agent, pipeline, or internal tool, and you can speak fluently to the engineering decisions (not just the workflow decisions) behind it.

What You'll Do

• Discover & scope: Embed with a business function, run structured technical discovery, and turn an ambiguous use case idea into a scoped build. Build in production: Independently design, write, test, and deploy Claude-powered agents, automations, and internal tools (Claude Code, Claude Cowork, Claude API/Agent SDK, or agentic frameworks built on Claude) — owning the full lifecycle from first commit to something running unattended in production.

• Engineer for reliability, not demos: Make and defend real engineering decisions — model selection, context/caching strategy, evals, human-in-the-loop checkpoints, error handling, cost forecasting — the difference between a working prototype and something that survives contact with real data and real users.

• Measure: Establish a baseline before every build; define the metric that proves impact (time saved, error rate, throughput) and instrument for it from day one.

• Enable: Leave each function more capable than you found it — train non-technical teams to identify and eventually build their own lightweight automations, without creating dependency on this role.

• Influence: Translate between business problems and technical tradeoffs; move skeptical stakeholders from "prove it" to adoption; align priorities with senior leaders and company OKRs.

• Scale patterns: Turn what works in one function into a reusable playbook other teams — and other builders — can pick up.

What We're Looking For

• Production Claude experience (required): 2+ years hands-on building AI agents, automations, or internal tools professionally, with direct, independent, code-level work in Claude Code, the Claude API, Claude Skills/Agent SDK, or an agentic framework built on top of Claude. You should be able to walk us through a system you built, why you made the architecture choices you did, and what broke in production.

• Software engineering fundamentals: Comfortable writing and owning real code — not exclusively configuring no-code/automation platforms. You should be fluent in things like API integration, MCP, version control, testing, and debugging a system you didn't just prototype but actually run.

• Technical judgment: You surface model selection tradeoffs, caching and cost strategy, reliability/failure modes, and human-in-the-loop design without being asked — because you've had to make those calls before and lived with the consequences. You also know when a workflow's data sensitivity should change the build: wh

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