SINGLE GRAIN TEMPLATE

Single Grain•Los Angeles, CA

6d•Remote

About The Position

Single Grain is seeking an AI Automation Engineer to identify and eliminate company inefficiencies by designing, building, and deploying AI-powered systems. The goal is to increase capacity, shorten production timelines, and boost Revenue Per Employee. This role involves shadowing departments, mapping workflows, identifying high-ROI bottlenecks, and rapidly deploying automations. A key aspect will be contributing to the client-facing revenue agent by writing production code. The primary Key Performance Indicator (KPI) is to increase Revenue Per Employee by 100% within 12 months and generate over $250,000 in annualized efficiency value. This is a hands-on, build-and-deploy role focused on creating leverage, not a research, prompt-writing, or strategy position.

Requirements

Proven experience building systems that saved real time or money, with quantifiable results.
Operates at an AI Power User level, orchestrating multiple AI tools, designing prompt systems, connecting APIs, and building production automations.
Thinks in terms of leverage, not just task completion.
Quantifies everything, preferring rough numbers over no numbers.
Communicates clearly and drives adoption without direct authority.
Ability to interview stakeholders, translate problems into technical solutions, and train users.
A degree in CS, engineering, data, business, or a related field, or equivalent hands-on experience.

Nice To Haves

Experience in agency, operations, or client services environments.
Experience building tools that scaled across multiple teams.
Strong product instincts.

Responsibilities

Diagnose before building: Shadow departments, map workflows, and quantify inefficiencies in time and dollars before coding. Identify top automation opportunities ranked by ROI.
Ship production AI systems: Design and deploy AI agents and automations integrating LLMs (Claude, ChatGPT, Gemini), APIs, and workflow tools (Zapier, Make, custom scripts). Rapid prototyping and iteration are expected.
Contribute to client revenue agents: Make production code contributions to the live revenue agent and execute real deployments within the first 30 days.
Document everything: Create an SOP and Loom walkthrough (Camcorder Method) for every automation to enable teams to operate them independently.
Drive adoption: Train users clearly, gather feedback, iterate, and track usage, aiming for a 70%+ adoption rate within 30 days of each deployment.
Build the intake system: Establish an automation request and prioritization framework for ongoing opportunity surfacing and ranking.
Report leverage quarterly: Track and present recurring efficiency value, cycle time reductions, and RPE impact to leadership.