Actively recruiting / 46 applicants
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Jane Cervantes is in direct contact with the company and can answer any questions you may have. Email
Jane Cervantes, RecruiterSenior AI Product Engineer (Full Stack)
Remote • Contract • Long-Term • Performance-Based Upside
We're building the next generation of AI-powered software for small and medium-sized businesses.
We don't build marketing websites or generic CRUD applications. We build AI employees, autonomous workflows, internal operating systems, customer-facing AI products, and enterprise-grade automation that delivers measurable business outcomes.
If you've been looking for a team where you can work on cutting-edge AI projects instead of another dashboard, we'd love to talk.
What You'll Build
Examples of projects include:
- AI agents and autonomous workflows
- AI-powered SaaS applications
- Custom business operating systems
- Customer portals
- AI sales, support, and operations tools
- Internal productivity platforms
- LLM integrations
- Workflow automation
- RAG systems
- Multi-agent architectures
- Voice AI applications
Our Typical Tech Stack
You don't need experience with every technology below, but you should be comfortable learning quickly.
Frontend
- Next.js
- React
- TypeScript
- Tailwind CSS
Backend
- Node.js
- Supabase
- PostgreSQL
- REST APIs
- GraphQL (nice to have)
AI
- OpenAI
- Anthropic
- Gemini
- Vercel AI SDK
- MCP
- RAG
- AI Agents
- Prompt Engineering
Infrastructure
- Vercel
- GitHub
- Docker
- Cloudflare
- Stripe
- n8n
- Payload CMS (nice to have)
What We're Looking For
You:
- Ship products quickly without sacrificing quality.
- Think like a product engineer, not just a coder.
- Can own features from architecture through deployment.
- Enjoy solving difficult technical problems.
- Write clean, maintainable TypeScript.
- Are comfortable working directly with AI models and APIs.
- Communicate clearly in English.
- Can work independently with minimal management.
Bonus Points
Experience with:
- AI agent frameworks
- LangGraph
- CrewAI
- Model Context Protocol (MCP)
- Vercel AI SDK
- Retrieval-Augmented Generation (RAG)
- Vector databases
- Multi-tenant SaaS
- Real-time applications
- Voice AI
- Open-source AI contributions
What Success Looks Like
Within your first 90 days you'll have helped ship production AI systems that customers actually use.
We value shipping, ownership, and business impact over resumes and years of experience.
Compensation
Compensation is based on project work and includes a performance-based revenue share.
Our lead engineers earn 20% of project contract value (even on larger contracts - we like to overpay for great talent and effort) when they successfully own and deliver client engagements.
High performers receive consistent project opportunities and long-term collaboration.
Hiring Process
- Review of GitHub and portfolio
- 30-minute technical interview
- Paid technical assessment
- Paid trial project
- Long-term contract
To Apply
Please include:
- GitHub profile
- Portfolio or recent projects
- Resume or LinkedIn
- AI applications you've personally built
- Your strongest full-stack project
- Time zone
- Weekly availability
We care far more about what you've built than where you worked.