AI Product Engineer (Full Stack) – AI/LLM Applications

Location: United States; remote work aligned with U.S. Business Hours

Company

hirify.global is hiring for a remote AI product engineering role focused on building production-ready AI-powered applications.

What you will do

• Build and launch a production-ready web application from scratch, covering frontend development and backend architecture.
• Integrate Claude, OpenAI, Gemini, and other AI models into production workflows and product experiences.
• Develop scalable APIs, backend services, database structures, authentication, permissions, and real-time data flows.
• Implement prompt workflows, guardrails, hallucination handling, and failure recovery systems to improve AI reliability.
• Improve scalability, performance, uptime, data protection, and user experience while debugging production issues.
• Collaborate directly with leadership and product stakeholders to turn ideas and user feedback into technical solutions.

Requirements

• Strong full-stack development experience and a proven record of shipping real production products.
• Hands-on experience integrating AI and LLMs into applications, including understanding hallucinations, edge cases, and prompt reliability.
• Strong knowledge of APIs, backend systems, system architecture, and scalable product design.
• Experience with Supabase, Firebase, PostgreSQL, or similar backend platforms.
• Strong debugging and problem-solving skills, with the ability to work independently and take high ownership.
• Must be based in the United States and able to work U.S. business hours.

Nice to have

• Experience building AI agents, workflow automation systems, or SaaS platforms.
• Familiarity with Claude, OpenAI APIs, vector databases, and RAG workflows.
• Startup or MVP-to-production experience.
• Exposure to logistics, aviation, operational platforms, or membership systems.
• Experience with React, Next.js, TypeScript, Node.js, Vercel, Docker, and cloud deployments.

Culture & Benefits

• Fully remote flexibility within the United States.
• High ownership and autonomy.
• Direct impact on product and technical direction.
• Opportunity to build real AI products and scale them from MVP to production.
• Work with modern AI tooling and infrastructure.

Hiring process

• Initial screening call.
• Technical and systems design interview followed by a practical product build or AI scenario.
• Final interview, internal review, and offer.