Founding Engineer

Goodfit; Minnesota; On-site; USD 120,000 - 180,000; Full time

Job summary

InCommon is seeking an engineer to own the entire AI-driven hiring agent stack. You will collaborate with recruiters, diagnose what’s broken, and ship hand-held tools by the week. You will oversee sourcing, screening, interview assist, and fit evaluation—plus an eval harness to keep the system honest.

You will work hands-on with SLMs, LoRA, quantization, tokenizers, and the trade-offs of model serving, delivering end-to-end production-grade solutions for deterministic hiring workflows.

Qualifications

• 2-4 years of engineering experience with a focus on AI-native solutions.

Responsibilities

• Build and own the full agent stack (sourcing, screening, interview assist, fit evaluation).
• Develop the eval harness that keeps the system honest.
• Create workflow surfaces for recruiters to use the built tools, end-to-end.

Skills

Agent frameworks

Full-stack development

Sourcing & screening

SLMs & model basics

Recruiter collaboration

Tools

LoRA

Quantization

Tokenizers

Eval harness

Serving trade-offs

Job description

We started with one obsessive question: can hiring be made deterministic? We've been building toward that answer since 2023, and we need the person who's going to build the engine that gets us there.

The Job

You’ll sit with recruiters on Monday, figure out what's broken, and ship something into their hands by Thursday. No Jira tickets, no design specs handed to you — just a hard problem and full ownership.

You’ll build and own the full agent stack — sourcing, screening, interview assist, fit evaluation — plus the eval harness that keeps it honest. When recruiters need a workflow surface to use what you built, you’ll build that too, front to back. When a fine-tuned 3B model beats a frontier API call, you’ll know and ship that instead.

You're our person if…

• 2-4 years of engineering experience, AI-native by instinct — reaching for agent frameworks before being asked

• Shipped a real agent system: tool use, memory, evals, and the unglamorous plumbing included

• Built full-stack applications end to end and owned them in production

• Hands-on with SLMs — LoRA, quantization, tokenizers, serving trade-offs, no bluffing

• Can talk to recruiters like a human being — they’re your closest collaborators

• The determinism question makes you want to find out, not roll your eyes

Why this?

Most AI jobs are "add a chatbot and call it AI-native." This isn’t that. Your decisions become the architecture. The good ones and the embarrassing ones.

If that sounds fun, let’s talk.

InCommon is an equal opportunity employer. We're building a diverse team because it makes us better at the problem we're trying to solve.