Founding FDE

About Operon

Agentic data layer for manufacturing & process industries.

Tech description:

We are looking for founding engineers who have deep knowledge in computer vision.

**Problems we are tackling**

- **Multimodal perception at scale** ensembles of detection and segmentation models
that parse huge, dense industrial documents into objects and relationships, with all the
real-world long tail: scale, noise, near-duplicates, decades-old scans. We're moving
from a modular model stack toward end-to-end transformers that predict structure directly.

- **Topology** recovering true topology (what connects to what) from
imperfect detections, and reconciling it against engineering standards into one coherent
model of the plant.

- **A compounding data flywheel** — an agent + retrieval layer over the graph, a
human-in-the-loop review surface that turns every correction into labels, and —
increasingly — using the structured data we generate to **train our own models**. Every
document processed makes the next one easier.

- **Knowledge Infrastructure** — building evolving knowledge context layer with updating data inputs, supporting agent workflows & accurate data query.

Job description:

**Founding Forward Deployment Engineer**

Operon is building the context layer for AI agents in industrial enterprise, the infrastructure that lets AI actually understand what's happening on a job site, in a facility, or across a fleet of equipment. We're four months old, YC-backed, and we're deploying our first product in the Process and Manufacturing Industry. This is not a polish-and-ship role. You'll be on the ground with customers, figuring out how our software fits into messy real-world workflows, and feeding that directly back into what we build.

**What you’ll have**

* Full ownership of projects.
* You will define what “Forward Deployed Engineering” means at Operon.

**What You’ll Do**

* Embed with customers to understand engineering workflows at the source.
* Ship production code across backend, frontend, data pipelines, and AI workflows.
* Translate ambiguous customer pain into durable product abstractions.
* Debug failures in real environments.
* Work directly with the founder on product, architecture, customer deployment, and technical strategy.