Forward Deployed Engineer – Applied AI

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 11%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Banyan Software

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🤝 B2B

🏢 Enterprise

💰 $20k Debt Financing on 2023-01

B2B • Enterprise

Banyan Software is a company dedicated to acquiring and nurturing successful enterprise software businesses, preserving the legacy of founders while fostering growth and innovation. Founded in 2016, Banyan adopts a buy, hold and grow for life strategy, focusing on businesses that dominate niche markets. With a global workforce of over 750 employees across the US, Canada, UK, Europe, Australia, and New Zealand, Banyan aims to provide a permanent home for these software companies, supporting their employees and customers in the process.

📋 Description

• 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

• 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

• 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

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