Remote AI Engineering Lead: Scale RAG & Agentic AI

Primetag; United States; Remote; USD 180,000 - 260,000; Full time

Benefits offered by this job

Comprehensive medical insurance

Fully remote role with European core:

Nomad-style offices across Europe

Job summary

Primetag is seeking a senior, hands-on AI platform leader to drive the technical direction of our creator marketing agentic AI platform. You will scale retrieval systems, shape architecture, and push quality and cost efficiency, with growth into broader team leadership over time.

You will optimize RAG pipelines across billions of data points and millions of creators, build new capabilities, and partner with Product to align roadmaps.

Qualifications

• Senior-level experience designing and operating AI or machine learning systems at scale.
• Deep knowledge of retrieval-augmented generation, embeddings, and large language model architectures.
• Strong engineering background in Python and modern backend or data systems.
• Track record of shipping production AI products with measurable quality and cost outcomes.
• Ability to operate hands-on while influencing broader technical direction.

Responsibilities

• Scale existing RAG systems by optimizing retrieval across billions of data points, millions of creators, and complex multi-tenant use cases.
• Build new capabilities including agentic workflows, client-specific knowledge bases, real-time data synthesis, and MCP integrations.
• Set the technical bar for AI engineering, driving quality, reliability, and cost optimization across the stack.
• Evaluate technical initiatives through customer value, cost, and strategic impact rather than engineering elegance alone.
• Partner closely with Product and the AI squad to unblock work and align on roadmap priorities.

Skills

AI/ML at scale

RAG systems

Python

Backend data systems

Production AI

Job description

Primetag is seeking a senior, hands-on AI platform leader to drive the technical direction of our creator marketing agentic AI platform. You will scale retrieval systems, shape architecture, and push quality and cost efficiency, with growth into broader team leadership over time.

You will optimize RAG pipelines across billions of data points and millions of creators, build new capabilities, and partner with Product to align roadmaps.