Role Description
Craft is the AI Sales & CX Platform for the trillion-dollar home improvement industry. We deploy AI agents into complex, operationally intensive enterprises, and we need engineers who can take a customer from zero to value, on-site, in the real world.
We're a fully in-office team based in NYC shaped by two core values:
- Asymmetric warfare. We've outshipped and outsold VC-backed companies that raised half a billion dollars. We win by making unconventional decisions that prove correct, repeatedly.
- Long-term thinking. We align fully with our customers, build durable partnerships, and are building a generational company, not chasing a quick exit.
What you'll do
- Own end-to-end deployment for enterprise customers: integrations with CRMs, FSMs, and VoIP systems, AI agent configuration, and go-live
- Be on-site with customers during critical onboarding phases. You're not working from a ticket queue, you're in the room
- Translate patterns across deployments into product improvements
- Build internal tooling to make future deployments faster and more repeatable
What we're looking for
- Strong engineer who loves being close to customers: Python, REST APIs, webhooks, data pipelines
- High agency in ambiguous situations; you figure things out without a playbook
- Can translate technical concepts for operators who've never touched a CRM
- Comfortable with ~25% travel to customer sites
- We hire for slope: credentials don't matter, learning speed does
Why join us
- You own outcomes, and features are how you get there. When an enterprise goes live and starts seeing results, that's on you
- More real-world AI deployment scenarios in 6 months than most engineers see in years
- Profitable and founder-owned: competitive salary + unusually generous equity
Compensation
- $130,000 – $180,000 + meaningful equity
- Full medical, dental, vision
- Unlimited PTO
About Forward Deployed Engineering
Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.
Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.
Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.
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