Role Overview

The AI Systems & Acceleration Engineer focuses on building reusable systems, tooling, and acceleration layers that enable rapid AI experimentation. This role exists to turn fast-moving ideas and demos into a structured, scalable, and product-ready foundation-without slowing down innovation.

The position reports directly to the CEO and is part of a small, high-impact AI innovation and experimentation group.

Key Responsibilities

AI Experimentation Systems

• Design and build reusable AI experimentation infrastructure, including prompt and agent structure templates.
• Abstract tool-calling mechanisms and workflow orchestration patterns.
• Establish standardized approaches for multi-model usage, context management, and agent collaboration.

Vibe Coding Acceleration

• Build internal frameworks to accelerate demo creation and rapid prototyping.
• Reduce repetitive work by standardizing common components such as configuration, logging, and execution pipelines.
• Continuously shorten the time from idea to first working demo.

Automation & Experiment Stability

• Introduce lightweight automation mechanisms, including prompt regression testing and agent behavior consistency checks.
• Manage the lifecycle of demos by identifying which experiments should be reused, iterated on, or deprecated.

Productization Support

• Support the transition from experimental code to maintainable, product-ready components.
• Assist in technical refinement and handoff when successful demos move toward full product development.

Qualifications

Required

• Strong system-level thinking and abstraction abilities.
• Hands-on experience with at least one full-stack development environment (e.g., Python, Node.js).
• Practical experience with AI agents, workflows, or orchestration systems.
• Strong focus on improving development efficiency and reusability.

Nice to Have

• Experience building internal platforms, developer tools, or prototyping frameworks.
• Strong interest in Developer Experience (DX).
• Comfortable working in fast-paced, iterative environments with minimal upfront specifications.