Forward Deployed Engineer - Applied AI

About the role

Banyan Software is the best permanent home for software businesses that serve specialized industries, their employees, and their customers. With a buy-grow-and-hold-for-life approach and a permanent capital base, Banyan acquires and grows companies worldwide, honoring founder legacies and helping portfolio companies modernize through shared AI expertise and operational discipline. Founded in 2016, Banyan operates more than 120 portfolio companies across North and South America, Europe, and APAC, and has appeared on the Inc. 5000 list for six consecutive years. The Banyan Software Foundation, endowed with $100 million in Banyan stock, leverages technology to build a greener and more equitable world.

About the role

Forward Deployed Engineer, Applied AI

Medicat builds MedicatOne, the EHR used by college health and counseling centers across the US. Banyan Software acquires and grows vertical software companies like ours, and we're investing in AI that reaches clinicians and students in production.

This is an engineering role first. You will write production code most days: LLM integrations, automations, data workflows and the APIs that connect them to MedicatOne. You'll also sit close to our clinic customers and internal teams, turning what you see in their workflows into working software, often in days, not quarters.

If you're happiest owning a roadmap and writing specs for others to build, this isn't the role. If you want to be the person who ships the feature, debugs it with the customer on the call, and hardens it for HIPAA, keep reading.

What you'll do

Expect roughly 70% hands-on engineering and 30% embedded with customers and internal teams.

- Build and ship AI features end to end. Design, code, test and deploy LLM-powered features in MedicatOne: prompt design, tool calling, retrieval where it earns its place, and evaluation harnesses.

- Pick the simplest reliable solution. Sometimes that's an LLM, often it's plain code.

- Integrate with real clinical data. Write the services, SQL and data pipelines that move PHI safely between MedicatOne, customer systems and model providers.

- Deploy alongside customers. Join clinic implementation and discovery calls as the technical lead, scope what can be built, prototype against their data, and stay through go-live.

- Embed with internal teams. Find and automate repetitive work, and help analysts and developers get the most out of AI tools.

- Own production quality. Instrument, monitor and debug what you ship: latency, cost, accuracy and failure modes. Write evals so regressions are caught before customers see them.

- Make AI safe for healthcare. Implement HIPAA-compliant patterns for PHI handling, logging, access control, de-identification and vendor data boundaries.

- Harden internal tools. Review and productionize AI tools built by non-engineering teams before they touch customer data.

- Feed the roadmap with evidence. Bring back what you learned in the field as working prototypes and technical recommendations, not slide decks.