Forward Deployed Engineer – Applied AI

Banyan Software

. Design, code, test, and deploy LLM-powered features in MedicatOne .

Posted 11/5/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying LLM-powered features while ensuring HIPAA compliance and effective handling of PHI. Proficient in backend development, SQL, and production system design with a focus on security and data flow.

Highest-signal resume keywords

Backend Development in Python, C#/.NET, or TypeScript/NodeHands-On Experience with LLM APIsProduction SQL and Data Pipeline DevelopmentHIPAA Compliance and PHI HandlingREST API Design and Third-Party Integrations

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Backend DevelopmentSQLData PipelinesLLM APIsPrompt DesignFunction/Tool CallingREST API DesignAutomated TestingCI/CDProduction Code Shipping

Soft Skills

Technical CommunicationProblem SolvingCollaboration

Tools & Technologies

AzureAWSGitOpenAIAnthropicAzure OpenAIHL7 v2FHIR

Industry Keywords

B2B SaaSPHIPIIData SecurityMulti-Tenancy

Tech Stack

Tools & technologies

AWSAzureNode.jsPythonSQLTypeScript.NET

About the role

Key responsibilities & impact

Design, code, test, and deploy LLM-powered features in MedicatOne
Develop prompt designs, tool calling, retrieval solutions, and evaluation harnesses
Select the simplest reliable solution, using plain code when appropriate
Write services, SQL, and data pipelines to move PHI safely between MedicatOne, customer systems, and model providers
Join clinic implementation and discovery calls as technical lead
Scope solutions, prototype against customer data, and support customers through go-live
Embed with internal teams to identify and automate repetitive work
Help analysts and developers maximize AI tools
Instrument, monitor, and debug production systems for latency, cost, accuracy, and failure modes
Write evaluations to catch regressions before customers encounter them
Implement HIPAA-compliant PHI handling, logging, access control, de-identification, and vendor data boundaries
Review and productionize AI tools built by non-engineering teams
Convert field learnings into working prototypes and technical recommendations

Requirements

What you’ll need

3+ years as a software engineer shipping production code in B2B SaaS, with an individual-contributor track record
Still writes code every week
Strong in at least one backend language: Python, C#/.NET, or TypeScript/Node; comfortable reading the others
Hands-on production experience with LLM APIs, including OpenAI, Anthropic, or Azure OpenAI
Experience with prompt design and function/tool calling
End-to-end production system design, including data flow, security, and multi-tenancy
Production SQL, schema design, and data pipelines against relational databases
REST API design, authentication, webhooks, and third-party integrations
Git, code review, automated testing, CI/CD, and deployment to Azure or AWS
Experience handling PHI, PII, financial, or similarly protected data, including required access controls and audit trails
Ability to explain technical trade-offs to clinic directors or analysts and then build the solution
Authorized to work in and resides in the US; visa sponsorship unavailable
Nice to have: RAG, embeddings, vector databases, HL7 v2, FHIR, HIPAA experience, Forward Deployed/Solutions Engineering/implementation-engineering experience, LLM evaluation and observability tooling, agent frameworks or MCP, college/student/behavioral health software experience, and open-source contributions or a public portfolio of shipped AI projects

Benefits

Comp & perks

Production engineering work on AI features that reach clinicians and students in production
Opportunity to work closely with clinic customers and internal teams
Work on applied AI, healthcare technology, and HIPAA-compliant systems
Exposure to LLM integrations, automations, data workflows, and APIs
Inclusive workplace and equal employment opportunities
Accommodation available during the recruitment process