Client-Embedded AI Product Engineer

Tribe AI; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Tribe AI in the United States seeks a Forward-Deployed AI Product Engineer who owns the full loop from user discovery to shipped product. You’ll embed with clients, observe end users, and translate learnings into AI-powered products that deliver real business impact.

You’ll collaborate with AI architects, infrastructure engineers, designers, and PMs to shape end-to-end experiences from early discovery to stable, client-facing applications.

Qualifications

• 5+ years building digital products and owning the full product loop.
• Strong full-stack ability: React, Next.js, TypeScript on the frontend; Python or Node.js on the backend.
• Comfortable integrating AI/LLM APIs and building products where AI is integral.
• Experience in startup or resource-constrained environments with fast, multi-hat problem solving.
• Exceptional communicator who makes users feel heard and explains complex ideas clearly.

Responsibilities

• Product Engineering & Delivery: Build full-stack features using modern frameworks (React, Next.js, Python) to solve real user problems with minimal complexity.
• Integrate AI/LLM capabilities into client-facing products with attention to latency, reliability, and user experience.
• Stand up backend services, APIs, and integrations quickly — prototype fast, then harden what works.
• Make pragmatic technical choices under time constraints; eliminate work when a simpler path exists.
• Help evolve prototypes into production-ready experiences with appropriate tests, logging, and performance tuning.

Skills

React

Next.js

TypeScript

Python/Node.js

Full-stack development

Tools

APIs

AI integration

Job description

Tribe AI in the United States seeks a Forward-Deployed AI Product Engineer who owns the full loop from user discovery to shipped product. You’ll embed with clients, observe end users, and translate learnings into AI-powered products that deliver real business impact.

You’ll collaborate with AI architects, infrastructure engineers, designers, and PMs to shape end-to-end experiences from early discovery to stable, client-facing applications.