Founding Forward Deployed Engineer

Atomic

2d•$200,000 - $250,000•Hybrid

About The Position

We are a stealth holding company acquiring and operating software businesses in overlooked, mission-critical industries. We are rebuilding these systems as AI-native from the inside out. This is a build shop with real customers, real revenue, and real P&Ls. The role involves being the AI engineer responsible for building industry-specific GPTs, embedding AI-native functionality into systems of record, migrating datasets, making the process repeatable for new companies, and managing AI talent across operating companies. The split is 90% building and 10% managing.

Requirements

You are a builder first. You've shipped things people actually use. Alone or as the clear technical lead.
You are a forward-deployed engineer. You'll fly to a customer site, sit in their office, and understand the business before you write a line of code.
You've been called a 10x engineer and it wasn't in a self-review.
You have strong opinions about when to fine-tune vs. prompt vs. RAG vs. agent vs harness and you can defend them with numbers.
You've built with the current frontier stack (Claude, GPT, Gemini, open models) in production, not just in a Jupyter notebook.
You are allergic to slide decks and comfortable with ambiguity, small teams, and unglamorous industries.

Responsibilities

Building the industry-specific GPT: the reasoning layer that encodes the domain expertise of each vertical we operate in.
Embedding AI-native functionality directly into our AI-native system of record: not bolt-on chatbots. Core workflow replacement. Agents that do the job.
Moving legacy systems of record datasets into new ai-native ones: Core workflow replacement. Agents that do the job.
Making it repeatable: Every new company we bring into the portfolio should benefit from the playbook, model stack, eval harness, and infra you build.
Managing AI talent across our operating companies: you'll be a player-coach for the AI engineers embedded at each sub.
Ship a working domain-specific agent into a live customer environment in your first 30 days.
Build the eval infrastructure that lets us measure whether these agents are actually replacing human workflows (not vibes).
Fine-tune, distill, or route across frontier + open models depending on the economics of each vertical.
Sit with customers. Watch them work. Instrument their workflows. Rebuild them.
Write the AI engineering playbook that every future portfolio company inherits on day one.