Applied AI Engineer
Company: CGS
Location: Location not specified (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-10-06
About this role
Applied AI Engineer
Remote
| $180,000–$210,000 base + equity | Full-time | 2 openings
Location:
US-based preferred
Offsites:
Twice per year
Experience:
8–10 years
Work authorization:
Candidates must have their own US work authorization
About the Company
This profitable, seed-stage career technology company is on a mission to give everyone access to great coaching. The company has built a curated network of experienced operator-coaches who work with managers and leaders at some of the world's leading technology companies. Around the human coaching relationship, the company is building a powerful software and AI layer capturing what is happening at work, giving coaches better context, and helping members turn coaching insights into meaningful action between sessions.
The result is an AI-native, human-centered challenger to the traditional coaching model, operating as a remote-first company across the US, Canada, and Latin America.
About the Role
We're looking for a product-minded full-stack engineer who knows how to put AI into the hands of real users. This is not an ML research, data science, or pure data engineering role. The focus is on building useful AI-powered product experiences and shipping them into production.
You'll join a small, highly experienced engineering team and work closely with the founders, product, design, and coaching network.
The two qualities that matter most are:
1. Exceptional AI development workflow
You know how to use modern AI coding tools effectively and, importantly, how to validate, test, automate, and improve their output. This will be assessed through a live LLM coding interview.
2. Critical thinking
You can clearly explain the technical decisions you've made, build a strong mental model of complex systems, and articulate what you would change with hindsight.
What You'll Own
- Build and ship AI-powered features used by real customers
- Develop full-stack product experiences ar...