AI Product Engineer

Role Description

At Pavago, one of our clients is hiring an AI Product Engineer (Full Stack) to build and scale a production-ready web application from the ground up. This is a hands-on product engineering role, not a support or maintenance position. You’ll take ownership across the entire product lifecycle:

• Frontend development
• Backend architecture
• AI/LLM integration
• APIs and data infrastructure
• Authentication and security
• Deployment and performance
• Product iteration and scaling

You’ll work closely with leadership to turn product ideas into working, production-ready software, ship quickly, learn from real usage, and continuously improve the platform. If you’re a builder who can independently take an AI-powered product from concept → MVP → production → scale, this role is a strong fit.

Qualifications

• Strong full-stack engineering experience across frontend and backend development
• Proven experience building and shipping production-level products
• Hands-on experience integrating AI/LLMs into real applications
• Strong understanding of system architecture, API design, data structures, and application performance
• Experience with Supabase or similar backend platforms
• Understanding of practical AI limitations, including hallucinations, failure states, edge cases, and output validation
• Strong knowledge of security best practices, including authentication, permissions, and data protection
• Strong debugging and problem-solving ability
• Ability to work independently and take end-to-end ownership of product development

Requirements

• Experience building AI agents
• Experience designing AI automation workflows
• Familiarity with Claude or similar LLMs in production
• Experience building SaaS products, operational platforms, and workflow applications
• Experience taking products from MVP to production
• Experience scaling applications after initial launch
• Exposure to aviation, logistics, and membership systems

Benefits

• Build an AI-powered product from the ground up
• End-to-end ownership across the full technology stack
• Direct involvement in product and architecture decisions
• Hands-on exposure to production LLM systems
• Opportunity to build AI workflows and agents around real-world use cases
• Work directly with leadership
• High autonomy and execution ownership
• Opportunity to take a product from MVP through production and scale
• Fully remote environment

Interview Process

• Initial Screening Call
• Technical & Systems Design Interview
• Practical Task – Product Build / AI Integration Scenario
• Final Interview
• Internal Review & Approval
• Offer & Onboarding

Company Description

If you are a strong full-stack engineer with built and shipped real production products, have hands-on experience integrating LLMs into applications, and understand AI hallucinations, edge cases, and guardrails, we’d love to hear from you.