Remote Forward-Deployed AI Architect - Production Systems Lead

tribe.ai; Myrtle Point (OR); Remote; USD 270,000 - 340,000; Full time

Benefits offered by this job

Fully Remote

Job summary

Tribe AI is seeking a Lead AI Architect to join our remote-first team. You’ll walk into enterprises, define production AI workflows, and own technical direction while staying hands-on to earn trust across engineering teams.

Design end-to-end AI applications with LLMs, RAG, and cloud infrastructure. Lead discovery sessions with executives, translate business problems into concrete plans, and raise the bar with reusable frameworks.

Qualifications

• 8+ years building production software.
• Deep experience shipping AI products into production.
• Strong Python engineering skills.
• Experience with modern AI frameworks, including agent systems, RAG, orchestration frameworks, vector databases, evaluation pipelines, and LLM APIs.
• Experience designing distributed cloud systems on AWS, Azure, or GCP.
• Strong systems thinking—you understand infrastructure as well as models.
• Excellent communication skills with technical and executive audiences.

Responsibilities

• Design production AI systems by architecting end-to-end AI applications using LLMs, RAG, agents, structured workflows, evaluation pipelines, and modern cloud infrastructure.
• Make pragmatic technical decisions around latency, reliability, observability, governance, and cost.
• Design systems that continue working after the demo.

Skills

Python engineering

LLM frameworks

RAG

agent systems

cloud infrastructure

executive communication

Tools

AWS

Azure

GCP

Job description

Tribe AI is seeking a Lead AI Architect to join our remote-first team. You’ll walk into enterprises, define production AI workflows, and own technical direction while staying hands-on to earn trust across engineering teams.

Design end-to-end AI applications with LLMs, RAG, and cloud infrastructure. Lead discovery sessions with executives, translate business problems into concrete plans, and raise the bar with reusable frameworks.