Forward Deployed Engineer - Applied AI

Banyan Software

2d

About The Position

Medicat builds MedicatOne, an EHR used by college health and counseling centers across the United States. This engineering-first role focuses on delivering production AI software for clinicians and students. The engineer will spend roughly 70% of their time on hands-on engineering and 30% embedded with customers and internal teams, translating real workflows into working software and supporting deployments through go-live.

The role involves building and deploying LLM-powered features, integrations, automations, data workflows, and APIs connected to MedicatOne. It also requires working with clinical data and protected health information, collaborating directly with clinics and internal teams, and ensuring shipped systems are reliable, observable, and compliant with healthcare privacy and security requirements. The position is intended for an individual contributor who regularly writes production code.

Requirements

• At least 3 years of experience as a software engineer shipping production code in B2B SaaS, with an individual-contributor track record and regular hands-on coding.
• Strong proficiency in at least one backend language: Python, C#/.NET, or TypeScript/Node; comfortable reading the others.
• Hands-on experience shipping production features using LLM APIs such as OpenAI, Anthropic, or Azure OpenAI, including prompt design and function/tool calling, and sound judgment about when not to use an LLM.
• Experience designing a production system from the ground up, including data flow, security, and multi-tenancy.
• Production SQL, schema design, and data-pipeline experience with relational databases.
• Experience with REST API design, authentication, webhooks, and third-party integrations.
• Production engineering practices including Git, code review, automated testing, CI/CD, and deployment to Azure or AWS.
• Experience building software that handles PHI, PII, financial data, or similarly protected data, including appropriate access controls and audit trails.
• Ability to explain technical trade-offs to customers and colleagues and then implement the solution.
• Authorized to work in and resident of the United States; visa sponsorship is not available.

Nice To Haves

• Experience with RAG, embeddings, and vector databases such as pgvector or Pinecone, and judgment about when retrieval justifies the added complexity.
• HL7 v2, FHIR, or EHR integration experience.
• Specific HIPAA experience.
• Prior Forward Deployed, Solutions Engineering, or implementation-engineering experience at a software company.
• Experience with LLM evaluation and observability tools such as LangSmith, Langfuse, or custom evaluation suites.
• Experience with agent frameworks or the Model Context Protocol (MCP).
• Experience with college health, student health, or behavioral health software.
• Open-source contributions or a public portfolio of shipped AI projects.

Responsibilities

• Design, code, test, and deploy end-to-end AI features in MedicatOne, including prompt design, tool calling, retrieval where appropriate, and evaluation harnesses.
• Select the simplest reliable solution, using conventional code instead of an LLM when appropriate.
• Build services, SQL, and data pipelines that safely move protected health information between MedicatOne, customer systems, and model providers.
• Lead technical participation in clinic implementation and discovery calls, scope potential work, prototype with customer data, and support solutions through go-live.
• Identify and automate repetitive work for internal teams and help analysts and developers use AI tools effectively.
• Instrument, monitor, and debug production systems, including latency, cost, accuracy, and failure modes; write evaluations to catch regressions.
• Implement HIPAA-compliant practices for PHI handling, logging, access control, de-identification, and vendor data boundaries.
• Review and productionize AI tools built by non-engineering teams before they handle customer data.
• Bring field learnings back to the roadmap as working prototypes and technical recommendations.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed