AI Engineer – Onsite – San Francisco, CA

RS Global Services; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

RS Global Services in San Francisco is seeking a full-time AI Engineer to own prompts, agents, evals, and pipelines behind user-facing features. You will turn product requirements into working AI components and ship production-ready systems that scale.

You will work at the intersection of product and platform, clearly distinguishing demo success from production readiness, and collaborate with Product Engineers and AI Platform to push features to users.

Responsibilities

• Build new AI features end to end, from prototype to production.
• Improve AI output quality through prompt engineering, model selection, retrieval, and evaluation.
• Design and run evals that measure real output quality, not just first impressions.
• Iterate fast on prompts, agent designs, and orchestration patterns.
• Partner with the Product Engineer to translate requirements into AI features that actually work.
• Partner with the AI Platform

Job description

Role Overview

One of our start-up clients is hiring a full-time AI Engineer to own the prompts, agents, evals, and pipelines behind user-facing features that ship to users.

You'll take product requirements and turn them into working prompts, agents, and pipelines. You'll evaluate them rigorously, iterate until they're production-ready, and keep improving them once they ship. This role sits at the intersection of product and platform: you decide what the AI should do, prove it works, and get it in front of users.

Because we're an early-stage company moving fast, we're looking for someone who can work quickly through ambiguous AI problems, measure output quality, and ship only when the system is reliable enough for production. This is an in-person role, 5 days a week in our office. The ability to tell the difference between "looks good in the demo" and "works in production" is essential.

Key Responsibilities

• Build new AI features end to end, from prototype to production.
• Improve AI output quality through prompt engineering, model selection, retrieval, and evaluation.
• Design and run evals that measure real output quality, not just first impressions.
• Iterate fast on prompts, agent designs, and orchestration patterns.
• Partner with the Product Engineer to translate requirements into AI features that actually work.
• Partner with the AI Platform