AI Product Engineer

We bring startups and disruptive tech companies to the local market, offering engineers the opportunity to work on innovative, high-impact products. Join us and become a member of their R&D team while we take care of employment, HR support, a benefits package, and an enjoyable work environment.

HoneyBook is the leading client relationship platform for independent businesses. It powers billions of client interactions through tools for attracting leads, connecting with clients, booking projects, and managing payments. With HoneyBook, any independent professional can scale themselves and their business.

Since the company was founded in 2013, HoneyBook members have built over 25 million client relationships and processed $11+ billion in payments on the platform. By providing an integrated suite of tools, HoneyBook simplifies workflow for independent professionals, serving as a center of gravity that streamlines operations from initial contact to final payment.

We're looking for a hands-on engineer with a strong core technical foundation and high AI leverage. You'll build and ship agentic workflows and shape how AI is adopted across the organization.

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• Work in tight build-measure-learn cycles on greenfield projects: MVP in days, validate, iterate or kill fast
• Evaluate emerging AI tools and technologies, run PoCs, and recommend what's worth adopting
• Build and maintain prototypes, plugins, and integrations with internal platforms (e.g., CI/CD pipelines, IDEs, documentation and test generation, code review, bug fixing)
• Build and maintain MCP servers and data-serving layers that empower AI agents
• Help shape AI usage standards: prompt engineering patterns, model selection, and guardrails around security and compliance
• Share knowledge and support other engineers in adopting AI-augmented workflows through pairing, examples, and internal docs
• Transition into more mature, large-scale products after successful greenfield delivery

Software engineering core

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• 5+ years of software engineering experience across production systems
• Language-agnostic mindset, comfortable picking up new stacks quickly. Experience with any of TypeScript, Python or Go is a plus
• Track record shipping and operating production-scale architectures
• Strong problem-solving and debug skills without relying fully on AI to do the thinking
• Solid system design, reliability, and failure handling experience
• Comfortable across multiple languages; able to jump into new stacks quickly

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AI-native workflows

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• AI is your default mode, not something you toggle on periodically.
• AI coding tools (Claude Code, Cursor, Copilot or Codex) are core to your daily workflow
• You have a comprehensive agent setup: you manage CLAUDE.md / AGENTS.md files, curate your own agent skills, use MCP servers, and use agent plugins
• You use spec-driven development workflows (OpenSpec, SpecKit, Kiro or your own equivalent)
• You know how to teach and guide agents through prompts, context, examples, and iterative refinement
• Understanding of LLM capabilities and limitations, when AI adds value and when it doesn't
• You manage token economy, AI budget consciously and monitoring using tools (e.g., langfuse, custom telemetry)
• Agentic system design, multi-step workflows, tool calling, state management, memory, context window optimization
• Knowledge of security and compliance considerations around AI (e.g., data leakage, model risk)
• You validate AI-generated code as any engineer's PR

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Experimental mindset

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• Proactive: you take ownership, propose solutions, and ramp into new projects quickly
• Adaptable: comfortable in a fast-changing environment, eager to learn new tools and approaches
• Collaborative: effective in small teams and larger cross-functional groups, comfortable working across departments
• Experimental: you compare tools, understand model limitations, and know when AI makes things worse

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Strategic thinking

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• Ability to translate AI capabilities into business value
• Experience driving AI adoption beyond your team
• Product thinking: trade-offs around quality, latency, cost, and user impact

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• Production experience integrating LLMs into products
• Familiarity with RAG pipelines and retrieval patterns
• Working experience with cloud AI services (AWS Bedrock, Azure OpenAI, or GCP Vertex AI)
• Experience with agentic frameworks (LangChain, CrewAI, or similar)
• Open-source AI tooling contributions
• Prior experience in a developer enablement, DevEx

The opportunity at HoneyBook is huge. Our primary customers today are creative businesses that generate $150B in revenue per year in the US. Founded in 2013, HoneyBook is based in San Francisco and Tel Aviv, has raised $498M, and is funded by Tiger Global Management, Norwest Venture Partners, Aleph, Hillsven Capital, OurCrowd, Durable Capital Partners LP, Vintage Investment Partners, Battery Ventures, Citi Ventures, Zeev Ventures, and 01 Advisors.

Here are our core values:
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• People come first: We prioritize people as we explore opportunities and work through challenges
• Raise the bar: We push for greatness — for ourselves, each other, and our members
• Own it: Trust and ownership let us make decisions with confidence
• We love what we do: We bring passion to our work and love what we create for our members
• Keep it real: Authenticity, respect, and transparency are at our core‍