Forward Deployed Engineer – Applied AI

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, test, and launch LLM-driven features within MedicatOne.

• Create prompt designs, tool invocation, retrieval solutions, and evaluation frameworks.

• Choose the most straightforward reliable solution, utilizing simple code when suitable.

• Construct services, SQL, and data pipelines to securely transfer PHI between MedicatOne, client systems, and model providers.

• Participate as the technical lead in clinic implementation and discovery discussions.

• Define solutions, prototype with customer data, and assist clients through the go-live process.

• Collaborate with internal teams to identify and automate repetitive tasks.

• Aid analysts and developers in optimizing the use of AI tools.

• Monitor, instrument, and troubleshoot production systems for latency, cost, accuracy, and failure modes.

• Draft evaluations to detect regressions prior to customer encounters.

• Implement HIPAA-compliant handling of PHI, including logging, access control, de-identification, and vendor data boundaries.

• Review and prepare AI tools developed by non-engineering teams for production.

• Transform field insights into functional prototypes and technical suggestions.

⛳️ Requirements

• Minimum of 3 years as a software engineer delivering production code in B2B SaaS, with a proven individual-contributor history.

• Continuously writes code on a weekly basis.

• Proficient in at least one backend language: Python, C#/.NET, or TypeScript/Node; comfortable reading the others.

• Practical experience with LLM APIs, such as OpenAI, Anthropic, or Azure OpenAI.

• Familiarity with prompt design and function/tool invocation.

• Experience in designing end-to-end production systems, including data flow, security, and multi-tenancy.

• Knowledge of production SQL, schema design, and data pipelines for relational databases.

• Proficient in REST API design, authentication, webhooks, and third-party integrations.

• Experience with Git, code reviews, automated testing, CI/CD, and deployment to Azure or AWS.

• Background in handling PHI, PII, financial, or similarly protected data, including necessary access controls and audit trails.

• Capable of articulating technical trade-offs to clinic directors or analysts and subsequently building the solution.

• Must be authorized to work in and reside in the US; visa sponsorship is not available.

• Preferred: Experience with RAG, embeddings, vector databases, HL7 v2, FHIR, HIPAA, Forward Deployed/Solutions Engineering/implementation-engineering, LLM evaluation and observability tools, agent frameworks or MCP, experience in college/student/behavioral health software, and contributions to open-source or a public portfolio of completed AI projects.

🏝️ Benefits

• Engaging in production engineering work on AI features that serve clinicians and students in real-world applications.

• Opportunity to collaborate closely with clinic customers and internal teams.

• Work on applied AI, healthcare technology, and systems compliant with HIPAA.

• Gain exposure to LLM integrations, automations, data workflows, and APIs.

• Join an inclusive workplace that offers equal employment opportunities.

• Accommodations available during the recruitment process.