About the role
About the Role
We’re looking for a Forward Deployed Engineer to work directly with mdhub’s most important customers, deploying, configuring, and scaling the first AI-native operating system for behavioral health clinics. This role lives at the intersection of engineering, product, and customer success.
mdhub is a full-stack platform where AI workers and clinical teams work together across admissions, clinical operations, and billing. Emma handles clinical documentation across millions of sessions. Sarah books patients into care 24/7. Eric 10x’s billing teams with AI-powered coding and claims. Our EHR, CRM, and RCM products tie it all together in one place. Your job is to make this entire system work seamlessly inside each customer’s environment.
This is a high-trust, high-autonomy role where you represent mdhub’s technical excellence on the ground. You’ll work directly with the founding team and be instrumental in shaping how our platform scales across diverse clinical environments.
What You'll Do
- Build and deploy mdhub's AI workers (Emma, Sarah, Eric) in customer environments - tuning model behavior, building custom prompt pipelines, and engineering the data flows that connect AI outputs to downstream systems like EHRs and claims engines.
- Build and maintain integrations between mdhub's platform and customer systems - EHRs, billing clearinghouses, scheduling APIs, and internal data pipelines - writing production code that handles real clinical data reliably.
- Write internal tooling, scripts, and automation that accelerate deployments - CLI tools, migration scripts, data validation pipelines, and monitoring dashboards that the team reuses across accounts.
- Debug complex production issues across the full stack - tracing failures across AI inference, API layers, third-party integrations, and customer infrastructure under real-time clinical pressure.
- Design and implement data migration pipelines that move clinics off legacy systems onto mdhub - transforming, validating, and loading patient records, billing histories, and clinical data at scale.
