Banyan Software provides the best permanent home for successful enterprise software companies, their employees, and customers. We are on a mission to acquire, build and grow great enterprise software businesses all over the world that have dominant positions in niche vertical markets. In recent years, Banyan was named the #1 fastest-growing private software company in the US on the Inc. 5000 and amongst the top 10 fastest-growing companies by the Deloitte Technology Fast 500. Founded in 2016 with a permanent capital base setup to preserve the legacy of founders, Banyan focuses on a buy and hold for life strategy for growing software companies that serve specialized vertical markets. AI Engineer (Healthcare SaaS) Location: Remote (must be inside the United States) Reports to: Chief Technology and Product Officer About Medicat (One of Banyan's Portfolio Companies) Medicat is building modern software infrastructure for healthcare organizations through our platform, MedicatOne. Our mission is to simplify complex healthcare operations through intuitive software, strong data infrastructure, and intelligent automation. As we expand our platform capabilities, we are investing in AI-driven features that improve how healthcare organizations interact with their data, workflows, and operational systems. We are seeking an experienced AI Engineer to help design and implement AI-native capabilities within MedicatOne. The Role This is a high-impact individual contributor role. This is a hands-on engineering role focused on building production-grade AI capabilities inside a growing healthcare SaaS platform. You will work closely with product leadership and engineering to architect and deploy AI-powered systems that interact with structured healthcare data and operational workflows. The role requires strong technical execution as well as fluency in data analytics and healthcare informatics concepts. This is a build-and-ship role where you will play a key part in translating AI opportunities into real product functionality. In this position, you will help to accelerate engineering performance and drive AI-enabled innovation across Medicat in our workflows and in our SaaS product. What You’ll Do AI System Development - Design and implement AI-powered capabilities within the MedicatOne platform - Integrate modern AI models and services into production workflows - Develop systems that interact with structured application data and APIs - Ensure AI features are reliable, performant, and secure Data & Informatics - Work with large datasets related to healthcare operations - Design systems that leverage structured data effectively - Build logic that enables intelligent interpretation of operational data - Collaborate with engineering on data pipelines, schemas, and analytics frameworks Platform Integration - Integrate AI capabilities into existing SaaS architecture - Work with backend engineers to ensure scalable system design - Optimize performance of data-intensive AI workflows - Contribute to platform-level architecture decisions Execution & Iteration - Ship production-ready AI features quickly and iteratively - Collaborate closely with leadership on prioritization and implementation - Help establish best practices for AI development within the organization What We’re Looking For Experience - 5+ years building production SaaS systems - Direct experience building and implementing AI/ML or LLM-based features - Strong experience working with structured data and analytics systems - Experience working with healthcare data or healthcare SaaS environments, including familiarity with the regulatory, privacy, and compliance considerations that shape technical decisions (HIPAA, PHI handling, de-identification) - Demonstrated ability to build and deploy systems end-to-end Technical Skills You should be comfortable with: - Working knowledge of modern AI infrastructure and patterns, including: - LLM API integration (OpenAI, Anthropic, or similar) in production environments - Retrieval-Augmented Generation (RAG): designing retrieval pipelines, chunking strategies, and grounding LLM responses in real data - Vector databases: embedding, indexing, and querying unstructured or semi-structured data - Data modeling and SQL - Data pipelines and analytics workflows and working with large structured datasets - API design and backend services - Working with large, structured datasets Experience with healthcare informatics standards or healthcare data environments is strongly preferred. What Success Looks Like - AI capabilities successfully integrated into the MedicatOne platform - Production-ready systems that interact effectively with operational data - High-quality implementations that balance accuracy, performance, and usability - Scalable architecture supporting future AI development Why Join Medicat - Work directly with company leadership on high-impact initiatives - Build meaningful AI capabilities in a real healthcare environment - High ownership and autonomy in a growing SaaS company - Opportunity to shape the future of AI within the platform Diversity, Equity, Inclusion & Equal Employment Opportunity at Banyan: Banyan affirms that inequality is detrimental to our Teams, associates, our Operating Companies, and the communities we serve. Our goal is to impact lasting change through our actions. Together, we unite for equality and equity. Banyan is committed to equal employment opportunities regardless of any protected characteristic, including race, color, genetic information, creed, national origin, religion, sex, affectional or sexual orientation, gender identity or expression, lawful alien status, ancestry, age, marital status, or protected veteran status and will not discriminate against anyone on the basis of a disability. We support an inclusive workplace where associates excel based on personal merit, qualifications, experience, ability, and job performance. The expected base salary for this position is: USD $90,000 - $120,000 excluding annual bonus and equity (when applicable). Salary is based on several factors including market conditions, location and may vary depending on job-related skills and experience. Diversity, Equity, Inclusion & Equal Employment Opportunity at Banyan: Banyan affirms that inequality is detrimental to our Global Teams, associates, our Operating Companies, and the communities we serve. As a collective, our goal is to impact lasting change through our actions. Together, we unite for equality and equity. Banyan is committed to equal employment opportunities regardless of any protected characteristic, including race, color, genetic information, creed, national origin, religion, sex, affectional or sexual orientation, gender identity or expression, lawful alien status, ancestry, age, marital status, or protected veteran status and will not discriminate against anyone on the basis of a disability. We support an inclusive workplace where associates excel based on personal merit, qualifications, experience, ability, and job performance. Recruitment Notice Banyan Software may use artificial intelligence (AI) tools to assist in screening and/or assessing applicants during the recruitment process. All hiring decisions are made by our team. Personal information submitted through your application will be collected and used for recruitment purposes in accordance with applicable privacy laws. Contact us at any time with questions about our process or to request accommodation. Beware of Recruitment Scams We have been made aware of individuals fraudulently posing as members of our Talent Acquisition team and extending fake job offers. These scams may involve requests for personal information or payment for equipment. Protect yourself by following these steps: - Verify that all communications from our recruiting team come from an @banyansoftware.com email address. - Remember, employers will never request payment or banking information during the hiring process. - If you receive a suspicious message, do not respond — instead, forward it to careers@banyansoftware.com and/or report it to the platform where you received it. Your safety and security are important to us. Thank you for staying vigilant.

• Own all engineering deliverables — quality, scalability, and on-time execution • Lead and manage the full engineering organization: AI Engineers, ML Engineers, MLOps, and Data Engineers • Establish and run Agile/Scrum processes: sprints, backlog grooming, ticketing, and release planning • Build a culture of accountability, experimentation, and continuous improvement • Define and standardize best practices across the full AI/ML lifecycle — from experimentation through deployment and monitoring • Architect and oversee a full ML platform: infrastructure, scalability, reliability, and rapid iteration • Design and build scalable, end-to-end ML solutions for predictions, recommendations, search, and growth systems • Evaluate experiments, document findings, select winning approaches, and roll them out team-wide • Contribute directly to system architecture and key technical decisions • Oversee model training, optimization, deployment, and performance monitoring • Drive data excellence: clean pipelines, strong governance, and actionable insights • Establish frameworks that integrate generative AI into engineering workflows • Join client calls as a senior technical voice, shaping solutions and building stakeholder trust • Partner with product managers and business leaders to translate business objectives into technical roadmaps • Present trade-offs clearly so clients understand what's being built and why it will move their business • Hire, coach, and mentor top-tier AI-first engineers and engineering leaders • Establish clear career paths, feedback loops, and performance standards • Scale the AI function across MLE, MLOps, and Data Engineering as the company grows

• Design, build, and deploy clinical AI agents that reason over patient context, invoke tools, and generate care recommendations. • Own reliability, observability, and cost efficiency of LLM-powered workflows at scale. • Build and optimize RAG pipelines over clinical knowledge bases, treatment protocols, and real-time patient data. • Develop evaluation frameworks: offline benchmarks, safety tests, regression suites, and LLM-as-judge pipelines wired into CI/CD. • Design multi-step agent orchestration: planning, memory, tool use, error recovery, and human-in-the-loop escalation paths. • Collaborate with clinical, product, and engineering teams to translate patient care needs into AI system design. • Stay at the forefront of AI and engineering best practices, continuously pushing the team to raise the bar on quality, performance, and architecture.

• Design, build, and deploy clinical AI agents that reason over patient context, invoke tools, and generate care recommendations. • Own reliability, observability, and cost efficiency of LLM-powered workflows at scale. • Build and optimize RAG pipelines over clinical knowledge bases, treatment protocols, and real-time patient data. • Develop evaluation frameworks: offline benchmarks, safety tests, regression suites, and LLM-as-judge pipelines wired into CI/CD. • Design multi-step agent orchestration: planning, memory, tool use, error recovery, and human-in-the-loop escalation paths. • Collaborate with clinical, product, and engineering teams to translate patient care needs into AI system design. • Stay at the forefront of AI and engineering best practices, continuously pushing the team to raise the bar on quality, performance, and architecture.